PHYSICAL CHEMISTRY: Intermolecular forces (Qs) Flashcards
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| 16322836812 | Although Phosphine molecules contain hydrogen atoms, there is no hydrogen bonding between phosphine molecules, why? (1) | Answer shown above. |  | 0 |
| 16322836813 | What are the three types of intermolecular forces? | • van der Waals (induced dipole-dipole) • dipole-dipole (permanent) • H-bonding | 1 | |
| 16322838384 | What are van der Waals forces? | • Temporary dipoles between electrons in an atom • Causing an overall attraction • Bigger molecule = more e- --> stronger vdw |  | 2 |
| 16322836814 | What are dipole-dipole forces? | • Permenant dipoles, one of the atoms in the molecule (e.g a halide such as chlorine) is more electronegative (tendancy to attract a shared pair of electrons in a covalent bond) so forms a dipole-dipole molecule which is permenant. |  | 3 |
| 16322836815 | What are Hydrogen Bonds? | • Containing O, N, or F, which must be bonded to H • Hydrogen's delta positive being attracted to the loan pairs (which are negative) of another molecule. (bottom right F must have 2 more loan pairs) |  | 4 |
| 16322836816 | Explain why iodine has a higher melting point than fluorine (2) | Shown above. |  | 5 |
| 16322836817 | Boiling points of fluorine and hydrogen fluoride: -188c and 19.5c respectively Explain, in terms of bonding, why the boiling point of fluorine is very low (2) | Shown above. |  | 6 |
| 16322836818 | Draw H-bonding of hydrogen fluoride (3) | Shown above. |  | 7 |
| 16322836819 | Explain the shape of the graph in terms of bonding. | The H20 and HF have H-bonding, explaining why they have such high melting points as it takes more energy to break. The reason the other molecules begin to increase is because they have van der waals forces, which are much weaker, and increase in boiling points as the molecules get bigger as they have more electrons therefore more induced dipoles. |  | 8 |
Chapter 20 Vocab World Civilizations - The Global Experience (AP World History) Flashcards
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| 8747344632 | factories | European trading fortresses and compounds with resident merchants; utilized throughout Portuguese trading empire to assure secure landing places and commerce | 0 | |
| 8747358777 | El Mina | most important of early Portuguese trading factories in forest zone of Africa | 1 | |
| 8747363571 | Nzinga Mvemba | king of Kongo south of Zaire River from 1507 to 1543; converted to Christianity and took title Alfonso I; under Portuguese influence attempted to Christianize all of kingdom | 2 | |
| 8747377134 | Luanda | Portuguese factory established in 1520's south of Kongo; became basis for Portuguese colony of Angola | 3 | |
| 8747390709 | Royal African Company | chartered in 1660s to establish a monopoly over the slave trade among British merchants; supplied African slaves to colonies in Barbados, Jamaica, and Virginia | 4 | |
| 8747401772 | Indies piece | term used within the complex exchange system established by the Spanish for African trade; referred to the value of an adult male slave | 5 | |
| 8747414858 | triangular trade | Commerce linking Africa, the New World colonies, and Europe; slaves carried to America for sugar and tobacco transporte to Europe | 6 | |
| 8747427892 | Asante empire | established in Gold Coast among Akan people settled around Kumasi; dominated Oyoko clan; many clans linked under Osei Tutu after 1650 | 7 | |
| 8747439700 | asantehene | title taken by ruler of Asante empire; supreme civil and religious leader; authority symbolized by golden stool | 8 | |
| 8747449402 | Osei Tutu | member of Oyoko clan of Akan peoples in Gold Coast region of Africa; responsible for creating unified Asante Empire in 1701; utilized Western Firearms | 9 | |
| 8747471952 | Dahomey | kingdom developed among Fon or Aja peoples in 17th century; center at Abomey 70 miles from coast; under King Agaja expanded to control coastline and port of Whydah by 1727; accepted western firearms and goods in return for African slaves | 10 | |
| 8747492722 | Luo | Nilotic people who migrated from upper Nile valley; established dynasty among existing Bantu population in lake region of central eastern Africa; center at Bunyoro | 11 | |
| 8747508291 | Fulani | pastoral people of western Sudan; adopted purifying Sufi variant of Islam; under Usuman Dan Fodio im 1804, launched revolt against Hausa kingdoms; established state centered on Sokoto | 12 | |
| 8747546897 | Great Trek | movement of boer settlers in Cape Colony of southern Africa to escape influence of British colonial government in 1834; led to settlement of regions north of Orange River and Natal | 13 | |
| 8747561590 | mfecane | wars of 19th century in southern Africa; created by Zulu expansion under Shaka; revolutionized political organization of southern Africa | 14 | |
| 8747571343 | Swazi | New African state formed on model of Zulu chiefdom; survived mfecane | 15 | |
| 8747579181 | Lesotho | Southern African state that survived mcfecane; not based on Zulu model; less emphasis on military organization, less authoritarian government | 16 | |
| 8747594619 | Middle Passage | slave voyage from Africa to the Americas (16th-18th centuries); generally a traumatic experience for black slaves, although it failed to strip Africans of their culture | 17 | |
| 8747603712 | saltwater slaves | slaved transported from Africa; almost invariably black | 18 | |
| 8747607149 | Creole slaves | American-born descendants of saltwater slaves; result of sexual exploitation of slave woman or process of miscegenation | 19 | |
| 8747625897 | Obeah | african religious ideas and practices in the English and French Caribbean islands | 20 | |
| 8747629145 | Candomble | african religious ideas and practices in Brazil, particularly among the Yoruba people | 21 | |
| 8749755387 | vodun | African religious ideas and practices among descendants of African slaves in Haiti | 22 | |
| 8747639340 | Palmares | kingdom of runaway slaves with a population of 8000 to 10,000 people; located in Brazil during the 17th century; leadership was Angolan | 23 | |
| 8747646226 | Suriname | formerly a Dutch plantation colony on the coast of South America; location of runaway slave kingdom in the 18th century; able to retain independence despite attempts to crush guerrilla resistance | 24 | |
| 8747657375 | William Wilberforce | British statesman and reformer; leader of abolitionists movement in English parliament that led to end of English slave trade in 1807 | 25 |
AP Statistics Flashcards
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| 14006806093 | How do you check if there is outliers? | calculate IQR; anything above Q3+1.5(IQR) or below Q1-1.5(IQR) is an outlier | 0 | |
| 14006806094 | If a graph is skewed, should we calculate the median or the mean? Why? | median; it is resistant to skews and outliers | 1 | |
| 14006806095 | If a graph is roughly symmetrical, should we calculate the median or the mean? Why? | mean; generally is more accurate if the data has no outliers | 2 | |
| 14006806096 | What is in the five number summary? | Minimum, Q1, Median, Q3, Maximum | 3 | |
| 14006806097 | Relationship between variance and standard deviation? | variance=(standard deviation)^2 | 4 | |
| 14006806098 | variance definition | the variance is roughly the average of the squared differences between each observation and the mean | 5 | |
| 14006806099 | standard deviation | the standard deviation is the square root of the variance | 6 | |
| 14006806100 | What should we use to measure spread if the median was calculated? | IQR | 7 | |
| 14006806101 | What should we use to measure spread if the mean was calculated? | standard deviation | 8 | |
| 14006806102 | What is the IQR? How much of the data does it represent? | Q3-Q1; 50% | 9 | |
| 14006806103 | How do you calculate standard deviation? | 1. Type data into L1 2. Find mean with 1 Variable Stats 3. Turn L2 into (L1-mean) 4. Turn L3 into (L2)^2 5. Go to 2nd STAT over to MATH, select sum( 6. Type in L3 7. multiply it by (1/n-1) 8. Square root it | 10 | |
| 14006806284 | What is the formula for standard deviation? |  | 11 | |
| 14006806104 | Categorical variables vs. Quantitative Variables | Categorical: individuals can be assigned to one of several groups or categories Quantitative: takes numberical values | 12 | |
| 14006806105 | If a possible outlier is on the fence, is it an outlier? | No | 13 | |
| 14006806106 | Things to include when describing a distribution | Center (Mean or Median), Unusual Gaps or Outliers, Spread (Standard Deviation or IQR), Shape (Roughly Symmetric, slightly/heavily skewed left or right, bimodal, range) | 14 | |
| 14006806107 | Explain how to standardize a variable. What is the purpose of standardizing a variable? | Subtract the distribution mean and then divide by standard deviation. Tells us how many standard deviations from the mean an observation falls, and in what direction. | 15 | |
| 14006806108 | What effect does standardizing the values have on the distribution? | shape would be the same as the original distribution, the mean would become 0, the standard deviation would become 1 | 16 | |
| 14006806109 | What is a density curve? | a curve that (a) is on or above the horizontal axis, and (b) has exactly an area of 1 | 17 | |
| 14006806110 | Inverse Norm | when you want to find the percentile: invNorm (area, mean, standard deviation) | 18 | |
| 14006806111 | z | (x-mean)/standard deviation | 19 | |
| 14006806112 | pth percentile | the value with p percent observations less than is | 20 | |
| 14006806113 | cumulative relative frequency graph | can be used to describe the position of an individual within a distribution or to locate a specified percentile of the distribution | 21 | |
| 14006806114 | How to find and interpret the correlation coefficient r for a scatterplot | STAT plot, scatter, L1 and L2 (Plot 1: ON); STAT --> CALC --> 8:LinReg(a+bx) No r? --> 2nd 0 (Catalog) down to Diagnostic ON | 22 | |
| 14006806115 | r | tells us the strength of a LINEAR association. -1 to 1. Not resistant to outliers | 23 | |
| 14006806116 | r^2 | the proportion (percent) of the variation in the values of y that can be accounted for by the least squares regression line | 24 | |
| 14006806117 | residual plot | a scatterplot of the residuals against the explanatory variable. Residual plots help us assess how well a regression line fits the data. It should have NO PATTERN | 25 | |
| 14006806118 | regression line | a line that describes how a response variable y changes as an explanatory variable x changes. We often use a regression line to predict the value of y for a given value of x. | 26 | |
| 14006806119 | residual formula | residual=y-y(hat) aka observed y - predicted y | 27 | |
| 14006806120 | What method do you use to check if a distribution or probability is binomial? | BINS: 1. Binary: There only two outcomes (success and failure) 2. Independent: The events independent of one another? 3. Number: There is a fixed number of trials 4. Success: The probability of success equal in each trial | 28 | |
| 14006806121 | What method do you use to check if a distribution or probability is geometric? | BITS: 1. Binary: There only two outcomes (success and failure) 2. Independent: The events independent of one another 3. Trials: There is not a fixed number of trials 4. Success: The probability of success equal in each trial | 29 | |
| 14006806122 | n | number of trials | 30 | |
| 14006806123 | p | probability of success | 31 | |
| 14006806124 | k | number of successes | 32 | |
| 14006806125 | Binomial Formula for P(X=k) | (n choose k) p^k (1-p)^(n-k) | 33 | |
| 14006806126 | Binomial Calculator Function to find P(X=k) | binompdf(n,p,k) | 34 | |
| 14006806127 | Binomial Calculator Function for P(X≤k) | binomcdf(n,p,k) | 35 | |
| 14006806128 | Binomial Calculator Function for P(X≥k) | 1-binomcdf(n,p,k-1) | 36 | |
| 14006806129 | mean of a binomial distribution | np | 37 | |
| 14006806130 | standard deviation of a binomial distribution | √(np(1-p)) | 38 | |
| 14006806131 | Geometric Formula for P(X=k) | (1-p)^(k-1) x p | 39 | |
| 14006806132 | Geometric Calculator Function to find P(X=k) | geometpdf(p,k) | 40 | |
| 14006806133 | Geometric Calculator Function for P(X≤k) | geometcdf(p,k) | 41 | |
| 14006806134 | Geometric Calculator Function for P(X≥k) | 1-geometcdf(p,k-1) | 42 | |
| 14006806135 | Mean of a geometric distribution | 1/p=expected number of trials until success | 43 | |
| 14006806136 | Standard deviation of a geometric distribution | √((1-p)/(p²)) | 44 | |
| 14006806137 | What do you do if the binomial probability is for a range, rather than a specific number? | Take binomcdf(n,p,maximum) - binomcdf(n,p,minimum-1) | 45 | |
| 14006806138 | how do you enter n choose k into the calculator? | type "n" on home screen, go to MATH --> PRB --> 3: ncr, type "k" | 46 | |
| 14006806139 | μ(x+y) | μx+μy | 47 | |
| 14006806140 | μ(x-y) | μx-μy | 48 | |
| 14006806141 | σ(x+y) | √(σ²x+σ²y) | 49 | |
| 14006806142 | What does adding or subtracting a constant effect? | Measures of center (median and mean). Does NOT affect measures of spread (IQR and Standard Deviation) or shape. | 50 | |
| 14006806143 | What does multiplying or dividing a constant effect? | Both measures of center (median and mean) and measures of spread (IQR and standard deviation). Shape is not effected. For variance, multiply by a² (if y=ax+b). | 51 | |
| 14006806144 | σ(x-y) | √(σ²x+σ²y) --> you add to get the difference because variance is distance from mean and you cannot have a negative distance | 52 | |
| 14006806145 | calculate μx by hand | X1P1+X2P2+.... XKPK (SigmaXKPK) | 53 | |
| 14006806146 | calculate var(x) by hand | (X1-μx)²p(1)+(X2-μx)²p(2)+.... (Sigma(Xk-μx)²p(k)) | 54 | |
| 14006806147 | Standard deviation | square root of variance | 55 | |
| 14006806148 | discrete random variables | a fixed set of possible x values (whole numbers) | 56 | |
| 14006806149 | continuous random variables | -x takes all values in an interval of numbers -can be represented by a density curve (area of 1, on or above the horizontal axis) | 57 | |
| 14006806150 | What is the variance of the sum of 2 random variables X and Y? | (σx)²+(σy)², but ONLY if x and y are independent. | 58 | |
| 14006806151 | mutually exclusive | no outcomes in common | 59 | |
| 14006806152 | addition rule for mutually exclusive events P (A U B) | P(A)+P(B) | 60 | |
| 14006806153 | complement rule P(A^C) | 1-P(A) | 61 | |
| 14006806154 | general addition rule (not mutually exclusive) P(A U B) | P(A)+P(B)-P(A n B) | 62 | |
| 14006806155 | intersection P(A n B) | both A and B will occur | 63 | |
| 14006806156 | conditional probability P (A | B) | P(A n B) / P(B) | 64 | |
| 14006806157 | independent events (how to check independence) | P(A) = P(A|B) P(B)= P(B|A) | 65 | |
| 14006806158 | multiplication rule for independent events P(A n B) | P(A) x P(B) | 66 | |
| 14006806159 | general multiplication rule (non-independent events) P(A n B) | P(A) x P(B|A) | 67 | |
| 14006806160 | sample space | a list of possible outcomes | 68 | |
| 14006806161 | probability model | a description of some chance process that consists of 2 parts: a sample space S and a probability for each outcome | 69 | |
| 14006806162 | event | any collection of outcomes from some chance process, designated by a capital letter (an event is a subset of the sample space) | 70 | |
| 14006806163 | What is the P(A) if all outcomes in the sample space are equally likely? | P(A) = (number of outcomes corresponding to event A)/(total number of outcomes in sample space) | 71 | |
| 14006806164 | Complement | probability that an event does not occur | 72 | |
| 14006806165 | What is the sum of the probabilities of all possible outcomes? | 1 | 73 | |
| 14006806166 | What is the probability of two mutually exclusive events? | P(A U B)= P(A)+P(B) | 74 | |
| 14006806167 | five basic probability rules | 1. for event A, 0≤P(A)≤1 2. P(S)=1 3. If all outcomes in the sample space are equally likely, P(A)=number of outcomes corresponding to event A / total number of outcomes in sample space 4. P(A^C) = 1-P(A) 5. If A and B are mutually exclusive, P(A n B)=P(A)+P(B) | 75 | |
| 14006806168 | When is a two-way table helpful | displays the sample space for probabilities involving two events more clearly | 76 | |
| 14006806169 | In statistics, what is meant by the word "or"? | could have either event or both | 77 | |
| 14006806170 | When can a Venn Diagram be helpful? | visually represents the probabilities of not mutually exclusive events | 78 | |
| 14006806171 | What is the general addition rule for two events? | If A and B are any two events resulting from some chance process, then the probability of A or B (or both) is P(A U B)= P(A)+P(B)-P(A n B) | 79 | |
| 14006806172 | What does the intersection of two or more events mean? | both event A and event B occur | 80 | |
| 14006806173 | What does the union of two or more events mean? | either event A or event B (or both) occurs | 81 | |
| 14006806174 | What is the law of large numbers? | If we observe more and more repetitions of any chance process, the proportion of times that a specific outcome occurs approaches a single value, which we can call the probability of that outcome | 82 | |
| 14006806175 | the probability of any outcome... | is a number between 0 and 1 that describes the proportion of times the outcome would occur in a very long series of repetitions | 83 | |
| 14006806176 | How do you interpret a probability? | We interpret probability to represent the most accurate results if we did an infinite amount of trials | 84 | |
| 14006806177 | What are the two myths about randomness? | 1. Short-run regularity --> the idea that probability is predictable in the short run 2. Law of Averages --> people except the alternative outcome to follow a different outcome | 85 | |
| 14006806178 | simulation | the imitation of chance behavior, based on a model that accurately reflects the situation | 86 | |
| 14006806179 | Name and describe the four steps in performing a simulation | 1. State: What is the question of interest about some chance process 2. Plan: Describe how to use a chance device to imitate one repetition of process; clearly identify outcomes and measured variables 3. Do: Perform many repetitions of the simulation 4. Conclude: results to answer question of interest | 87 | |
| 14006806180 | What are some common errors when using a table of random digits? | not providing a clear description of the simulation process for the reader to replicate the simulation | 88 | |
| 14006806181 | What does the intersection of two or more events mean? | both event A and event B occur | 89 | |
| 14006806182 | sample | The part of the population from which we actually collect information. We use information from a sample to draw conclusions about the entire population | 90 | |
| 14006806183 | population | In a statistical study, this is the entire group of individuals about which we want information | 91 | |
| 14006806184 | sample survey | A study that uses an organized plan to choose a sample that represents some specific population. We base conclusions about the population on data from the sample. | 92 | |
| 14006806185 | convenience sample | A sample selected by taking the members of the population that are easiest to reach; particularly prone to large bias. | 93 | |
| 14006806186 | bias | The design of a statistical study shows ______ if it systematically favors certain outcomes. | 94 | |
| 14006806187 | voluntary response sample | People decide whether to join a sample based on an open invitation; particularly prone to large bias. | 95 | |
| 14006806188 | random sampling | The use of chance to select a sample; is the central principle of statistical sampling. | 96 | |
| 14006806189 | simple random sample (SRS) | every set of n individuals has an equal chance to be the sample actually selected | 97 | |
| 14006806190 | strata | Groups of individuals in a population that are similar in some way that might affect their responses. | 98 | |
| 14006806191 | stratified random sample | To select this type of sample, first classify the population into groups of similar individuals, called strata. Then choose a separate SRS from each stratum to form the full sample. | 99 | |
| 14006806192 | cluster sample | To take this type of sample, first divide the population into smaller groups. Ideally, these groups should mirror the characteristics of the population. Then choose an SRS of the groups. All individuals in the chosen groups are included in the sample. | 100 | |
| 14006806193 | inference | Drawing conclusions that go beyond the data at hand. | 101 | |
| 14006806194 | margin of error | Tells how close the estimate tends to be to the unknown parameter in repeated random sampling. | 102 | |
| 14006806195 | sampling frame | The list from which a sample is actually chosen. | 103 | |
| 14006806196 | undercoverage | Occurs when some members of the population are left out of the sampling frame; a type of sampling error. | 104 | |
| 14006806197 | nonresponse | Occurs when a selected individual cannot be contacted or refuses to cooperate; an example of a nonsampling error. | 105 | |
| 14006806198 | wording of questions | The most important influence on the answers given to a survey. Confusing or leading questions can introduce strong bias, and changes in wording can greatly change a survey's outcome. Even the order in which questions are asked matters. | 106 | |
| 14006806199 | observational study | Observes individuals and measures variables of interest but does not attempt to influence the responses. | 107 | |
| 14006806200 | experiment | Deliberately imposes some treatment on individuals to measure their responses. | 108 | |
| 14006806201 | explanatory variable | A variable that helps explain or influences changes in a response variable. | 109 | |
| 14006806202 | response variable | A variable that measures an outcome of a study. | 110 | |
| 14006806203 | lurking variable | a variable that is not among the explanatory or response variables in a study but that may influence the response variable. | 111 | |
| 14006806204 | treatment | A specific condition applied to the individuals in an experiment. If an experiment has several explanatory variables, a treatment is a combination of specific values of these variables. | 112 | |
| 14006806205 | experimental unit | the smallest collection of individuals to which treatments are applied. | 113 | |
| 14006806206 | subjects | Experimental units that are human beings. | 114 | |
| 14006806207 | factors | the explanatory variables in an experiment are often called this | 115 | |
| 14006806208 | random assignment | An important experimental design principle. Use some chance process to assign experimental units to treatments. This helps create roughly equivalent groups of experimental units by balancing the effects of lurking variables that aren't controlled on the treatment groups. | 116 | |
| 14006806209 | replication | An important experimental design principle. Use enough experimental units in each group so that any differences in the effects of the treatments can be distinguished from chance differences between the groups. | 117 | |
| 14006806210 | double-blind | An experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received. | 118 | |
| 14006806211 | single-blind | An experiment in which either the subjects or those who interact with them and measure the response variable, but not both, know which treatment a subject received. | 119 | |
| 14006806212 | placebo | an inactive (fake) treatment | 120 | |
| 14006806213 | placebo effect | Describes the fact that some subjects respond favorably to any treatment, even an inactive one | 121 | |
| 14006806214 | block | A group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments. | 122 | |
| 14006806215 | inference about the population | Using information from a sample to draw conclusions about the larger population. Requires that the individuals taking part in a study be randomly selected from the population of interest. | 123 | |
| 14006806216 | inference about cause and effect | Using the results of an experiment to conclude that the treatments caused the difference in responses. Requires a well-designed experiment in which the treatments are randomly assigned to the experimental units. | 124 | |
| 14006806217 | lack of realism | When the treatments, the subjects, or the environment of an experiment are not realistic. Lack of realism can limit researchers' ability to apply the conclusions of an experiment to the settings of greatest interest. | 125 | |
| 14006806218 | institutional review board | A basic principle of data ethics. All planned studies must be approved in advance and monitored by _____________ charged with protecting the safety and well-being of the participants. | 126 | |
| 14006806219 | informed consent | A basic principle of data ethics. Individuals must be informed in advance about the nature of a study and any risk of harm it may bring. Participating individuals must then consent in writing. | 127 | |
| 14006806220 | simulation | a model of random events | 128 | |
| 14006806221 | census | a sample that includes the entire population | 129 | |
| 14006806222 | population parameter | a number that measures a characteristic of a population | 130 | |
| 14006806223 | systematic sample | every fifth individual, for example, is chosen | 131 | |
| 14006806224 | multistage sample | a sampling design where several sampling methods are combined | 132 | |
| 14006806225 | sampling variability | the naturally occurring variability found in samples | 133 | |
| 14006806226 | levels | the values that the experimenter used for a factor | 134 | |
| 14006806227 | the four principles of experimental design | control, randomization, replication, and blocking | 135 | |
| 14006806228 | completely randomized design | a design where all experimental units have an equal chance of receiving any treatment | 136 | |
| 14006806229 | interpreting p value | if the true mean/proportion of the population is (null), the probability of getting a sample mean/proportion of _____ is (p-value). | 137 | |
| 14006806230 | p̂1-p̂2 center, shape, and spread | center: p1-p2 shape: n1p1, n1(1-p1), n2p2, and n2(1-p2) ≥ 10 spread (if 10% condition checks): √((p1(1-p1)/n1)+(p2(1-p2)/n2) | 138 | |
| 14006806231 | probability of getting a certain p̂1-p̂2 (ex. less than .1) | plug in center and spread into bell curve, find probability | 139 | |
| 14006806232 | Confidence intervals for difference in proportions formula | (p̂1-p̂2) plus or minus z*(√((p1(1-p1)/n1)+(p2(1-p2)/n2)) | 140 | |
| 14006806233 | When do you use t and z test/intervals? | t for mean z for proportions | 141 | |
| 14006806285 | Significance test for difference in proportions | 142 | ||
| 14006806234 | What is a null hypothesis? | What is being claimed. Statistical test designed to assess strength of evidence against null hypothesis. Abbreviated by Ho. | 143 | |
| 14006806235 | What is an alternative hypothesis? | the claim about the population that we are trying to find evidence FOR, abbreviated by Ha | 144 | |
| 14006806236 | When is the alternative hypothesis one-sided? | Ha less than or greater than | 145 | |
| 14006806237 | When is the alternative hypothesis two-sided? | Ha is not equal to | 146 | |
| 14006806238 | What is a significance level? | fixed value that we compare with the P-value, matter of judgement to determine if something is "statistically significant". | 147 | |
| 14006806239 | What is the default significance level? | α=.05 | 148 | |
| 14006806240 | Interpreting the p-value | if the true mean/proportion of the population is (null), the probability of getting a sample mean/proportion of _____ is (p-value). | 149 | |
| 14006806241 | p value ≤ α | We reject our null hypothesis. There is sufficient evidence to say that (Ha) is true. | 150 | |
| 14006806242 | p value ≥ α | We fail to reject our null hypothesis. There is insufficient evidence to say that (Ho) is not true. | 151 | |
| 14006806243 | reject Ho when it is actually true | Type I Error | 152 | |
| 14006806244 | fail to reject Ho when it is actually false | Type II Error | 153 | |
| 14006806245 | Power definition | probability of rejecting Ho when it is false | 154 | |
| 14006806246 | probability of Type I Error | α | 155 | |
| 14006806247 | probability of Type II Error | 1-power | 156 | |
| 14006806248 | two ways to increase power | increase sample size/significance level α | 157 | |
| 14006806249 | 5 step process: z/t test | State --> Ho/Ha, define parameter Plan --> one sample, z test Check --> random/normal/independent Do --> find p hat, find test statistic (z), use test statistic to find p-value Conclude --> p value ≤ α reject Ho p value ≥ α fail to reject Ho | 158 | |
| 14006806286 | Formula for test statistic (μ) |  | 159 | |
| 14006806250 | Formula for test statistic (p̂) (where p represents the null) | (p̂-p)/(√((p)(1-p))/n) | 160 | |
| 14006806251 | probability of a Type II Error? | overlap normal distribution for null and true. Find rejection line. Use normalcdf | 161 | |
| 14006806252 | when do you use z tests? | for proportions | 162 | |
| 14006806253 | when do you use t tests? | for mean (population standard deviation unknown) | 163 | |
| 14006806254 | finding p value for t tests | tcdf(min, max, df) | 164 | |
| 14006806255 | Sample paired t test | state--> Ho: μ1-μ2=0 (if its difference) plan --> one sample, paired t test check --> random, normal, independent do --> find test statistic and p value conclude --> normal conclusion | 165 | |
| 14006806256 | What does statistically significant mean in context of a problem? | The sample mean/proportion is far enough away from the true mean/proportion that it couldn't have happened by chance | 166 | |
| 14006806257 | When doing a paired t-test, to check normality, what do you do? | check the differences histogram (μ1-μ2) | 167 | |
| 14006806258 | How to interpret a C% Confidence Level | In C% of all possible samples of size n, we will construct an interval that captures the true parameter (in context). | 168 | |
| 14006806259 | How to interpret a C% Confidence Interval | We are C% confident that the interval (_,_) will capture the true parameter (in context). | 169 | |
| 14006806260 | What conditions must be checked before constructing a confidence interval? | random, normal, independent | 170 | |
| 14006806261 | C% confidence intervals of sample proportions, 5 step process | State: Construct a C% confidence interval to estimate... Plan: one sample z-interval for proportions Check: Random, Normal, Independent Do: Find the standard error and z*, then p hat +/- z* Conclude: We are C% confident that the interval (_,_) will capture the true parameter (in context). | 171 | |
| 14006806287 | What's the z interval standard error formula? |  | 172 | |
| 14006806262 | How do you find z*? | InvNorm(#) | 173 | |
| 14006806263 | How do you find the point estimate of a sample? | subtract the max and min confidence interval, divide it by two (aka find the mean of the interval ends) | 174 | |
| 14006806264 | How do you find the margin of error, given the confidence interval? | Ask, "What am I adding or subtracting from the point estimate?" So find the point estimate, then find the difference between the point estimate and the interval ends | 175 | |
| 14006806265 | Finding sample size proportions: When p hat is unknown, or you want to guarantee a margin of error less than or equal to: | use p hat=.5 | 176 | |
| 14006806266 | Finding the confidence interval when the standard deviation of the population is *known* | x bar +/- z*(σ/√n) | 177 | |
| 14006806267 | Checking normal condition for z* (population standard deviation known) | starts normal or CLT | 178 | |
| 14006806268 | Finding the confidence interval when the standard deviation of the population is *unknown* (which is almost always true) | x bar +/- t*(Sx/√n) | 179 | |
| 14006806269 | degrees of freedom | n-1 | 180 | |
| 14006806270 | How do you find t*? | InvT(area to the left, df) | 181 | |
| 14006806271 | What is the standard error? | same as standard deviation, but we call it "standard error" because we plugged in p hat for p (we are estimating) | 182 | |
| 14006806272 | a point estimator is a statistic that... | provides an estimate of a population parameter. | 183 | |
| 14006806273 | Explain the two conditions when the margin of error gets smaller. | Confidence level C decreases, sample size n increases | 184 | |
| 14006806274 | Does the confidence level tell us the chance that a particular confidence interval captures the population parameter? | NO; the confidence interval gives us a set of plausible values for the parameter | 185 | |
| 14006806275 | Sx and σx: which is which? | Sx is for a sample, σx is for a population | 186 | |
| 14006806276 | How do we know when do use a t* interval instead of a z interval? | you are not given the population standard deviation | 187 | |
| 14006806277 | Checking normal condition for t* (population standard deviation unknown) | Normal for sample size... -n -n<15: if the data appears closely normal (roughly symmetric, single peak, no outliers) | 188 | |
| 14006806278 | How to check if a distribution is normal for t*, population n<15 | plug data into List 1, look at histogram. Conclude with "The histogram looks roughly symmetric, so we should be safe to use the t distribution) | 189 | |
| 14006806279 | t* confidence interval, 5 step process | State: Construct a __% confidence interval to estimate... Plan: one sample t interval for a population mean Check: Random, Normal, Independent (for Normal, look at sample size and go from there) Do: Find the standard error (Sx/√n) and t*, then do x bar +/- t*(standard error) Conclude: We are __% confident that the interval (_,_) will capture the true parameter (in context). | 190 | |
| 14006806280 | margin of error formula | z* or t* (standard error) | 191 | |
| 14006806281 | When calculating t interval, what is it and where do you find the data? | x bar plus or minus t* (Sx/√n) -get x bar and Sx using 1 Var Stats -t*=Invt(area to the left, df) -population (n) will be given | 192 | |
| 14006806282 | What is it looking for if it asks for the appropriate critical value? | z/t* interval | 193 |
Flashcards
Flashcards
sexual reproduction in flowering plants Flashcards
Terms : Hide Images
| 8751684207 | Female parts of plant | carpel |  | 0 |
| 8751687924 | Male parts of plant | Stamen | 1 | |
| 8751684208 | Receptable | support floral parts | 2 | |
| 8751684209 | Sepal | protect the flower when it is a bud | 3 | |
| 8751684210 | Petals | attract insects to the flower for pollination | 4 | |
| 8751684212 | Anther | produces pollen grains from meiosis | 5 | |
| 8751684213 | Filament | transports food and water to anther via a vascular bundle | 6 | |
| 8751684215 | Stigma | where the pollen lands | 7 | |
| 8751684216 | Style | where the pollen tube grows | 8 | |
| 8751708555 | Ovary | contains one or more ovules | 9 | |
| 8751684217 | list the seven steps in sexual reproduction | gamete formation pollination fertilisation seed and fruit formation seed and fruit dispersal dormancy germination | 10 | |
| 8751684218 | what is the male gamete formation | developement of the pollen grain | 11 | |
| 8751684219 | what is the female gamete formation | developement of the embryo sac | 12 | |
| 8751684220 | how many chambers does an anther consist of | 4 | 13 | |
| 8751684221 | what are the chambers in an anther called | pollen sacs | 14 | |
| 8751684222 | what are the pollen sacs protected by | a protective epidermis and a fibrous layer | 15 | |
| 8751684223 | what is a tapetum | nutrient rich layer of cells located just inside the fibrous layer | 16 | |
| 8751684225 | where are the pollen mother cells (2n) located | pollen sacs | 17 | |
| 8751684226 | what is a microspore | pollen grain | 18 | |
| 8751684227 | what is a tetrad | a group of four haploid cells | 19 | |
| 8751684230 | in the developement of the pollen grain what does the pollen mother cell (2n) do | divides by meiosis to produce a group of four haploid cells called a tetrad | 20 | |
| 8751684231 | what does each tetrad do | breaks up to form four seperate haploid pollen grains | 21 | |
| 8751684232 | what happens to the pollen grain (n) nucleus | divides by mitosis to produce 2 haploid nuclei tube nucleus and generative nucleus | 22 | |
| 8751684228 | what does a tube nucleus form | the pollen tube | 23 | |
| 8751684229 | what does the generative nucleus form | the male gametes | 24 | |
| 8751684235 | what is the exine | thick outer wall of the mature pollen grain | 25 | |
| 8751684236 | what is the intine | thin inner wall of the pollen grain | 26 | |
| 8751684233 | what happens after the pollen grains have matured | walls of anther dry, shrivel and split, pollen grains are exposed on the outside of the anther | 27 | |
| 8751797959 | what is dehiscing | the splitting of the anther walls | 28 | |
| 8751819536 | what happens when the embryo sac (megaspore) mother cell undergoes meiosis? | forms 4 haploid cells | 29 | |
| 8751919534 | what happens to the 4 haploid cells formed from the megaspore mother cell? | 3 degenerate and die off and the remaining cell is the embryo sac (megaspore) | 30 | |
| 8751945183 | what happens to the eight haploid nuclei formed when the embryo sac divides by mitosis three times | 5 die and the others are the egg cell and 2 polar nuclei | 31 | |
| 8751684238 | what are the two walls of an ovule called? | integuments | 32 | |
| 8751684239 | what is a micropyle | small opening between the integuments through which a pollen tube can enter | 33 | |
| 8751684240 | what is the nucellus | cells inside the integuments that provide nutrients for later growth | 34 | |
| 8751684246 | what is pollination | the transfer of pollen from the anther to the stigma of a flower of the same species | 35 | |
| 8751684248 | what is self pollination | transfer of pollen from an anther to a stigma on the same plant | 36 | |
| 8751684249 | what is cross polination | transfer of pollen from an anther to a stigma of a different plant | 37 | |
| 8751684250 | 2 problems with self pollination | self fertilisation which is an extreme form of inbreeding and the seeds are less sturdy and less vigorous | 38 | |
| 8751684251 | 2 advantages of cross polinatation | cross fertilisation and seeds show more variation and vigour | 39 | |
| 8751684252 | disadvantage and example of wind pollination | wasteful of pollen e.g. grasses and oak | 40 | |
| 8751684258 | why is animal pollination a more advanced form of pollination | more precise in carrying the pollen directly to the stigma and less pollen is wasted | 41 | |
| 8752014093 | example of animal pollinated plants | orchids and dandelions | 42 | |
| 8751684254 | adaptions for wind pollination | petals are small, green and have no nectaries. Pollen is light, dry, small and produced in large amounts. Anthers are large, loosely attached to filament & found outside the plant. Stigmas are large, feathery and outside the petals | 43 | |
| 8751684260 | adaptions for animal pollination | petals are large, brightly coloured, scented and have nectaries. Pollen is heavy, large, sticks and produced in small amounts. Anthers are small, inside petals and firmly attached to filament. Stigmas are small, sticky and inside petals | 44 | |
| 8751684264 | what is hay fever | an allergic reaction to the inhalation of particles of harmless substances eg. pollen grains | 45 | |
| 8751684265 | what is an allergen | a substance that triggers the allergic reaction | 46 | |
| 8751684269 | what is fertilisation | fusion of male and female gametes to form a diploid zygote | 47 | |
| 8751684270 | what happens once pollen has landed on the stigma | produces a pollen tube which grows down through the style towards the ovule | 48 | |
| 8752069434 | what is chemotropism | the pollen grain grows towards chemicals released from the ovule | 49 | |
| 8751684273 | what happens to the generative nucleus the pollen tube grows down | divides by mitosis to form 2 haploid sperm nuclei | 50 | |
| 8752084225 | when does the tube nucleus die | when the pollen tube enters the ovule by the micropyle | 51 | |
| 8751684275 | what is double fertilisation | sperm nuclei enters the embryo sac. One fertiises the egg nucleus to form a a diploid zygote. The other joins with the two polar nuclei to form a triploid endosperm nucleus (3n) which acts as a food supply | 52 | |
| 8752110673 | what is an adaption of the male gametes | the presence of a pollen tube means that they can move towards the egg without the need for external water | 53 | |
| 8752123209 | In seed formation what does the ovule become | seed | 54 | |
| 8752126297 | In seed formation what do the integuments become | testa (seed coat) | 55 | |
| 8751684276 | In seed formation how does the zygote form the embryo | grow rapidly by mitosis | 56 | |
| 8751684277 | what does an embryo develop into | plumule, radicle and cotyledons | 57 | |
| 8751684278 | what is a plumule | future shoots | 58 | |
| 8751684279 | what is a radicle | future roots | 59 | |
| 8751684280 | what are cotyledons | seed leaf, becomes swollen with stored food | 60 | |
| 8751684281 | what happens to the triploid endosperm nucleus (3n) | divides rapidly by mitosis and absorbs the nucellus, acting as a food store | 61 | |
| 8751684283 | what are non endospermic seeds | the plant embryo increases in size absorbing all of the endosperm | 62 | |
| 8751684284 | what is an example of a non endospremic seed | peanut | 63 | |
| 8751684285 | what are endospermic seeds | the plant embryo increases in size but only absorbs some of the endosperm | 64 | |
| 8751684286 | what is an example of an endospermic seed | corn | 65 | |
| 8752167076 | what are monocot seeds | endospermic, one cotyledon, food obtained mainly from endosperm, send up a single shoot with no leaves | 66 | |
| 8752173882 | what are dicot seeds | non-endospermic, two cotyledons, food obtained mainly from cotyledons, send shoots with leaves | 67 | |
| 8751684287 | what is the fate of the zygote | becomes the embryo plant | 68 | |
| 8751684290 | what is the fate of the ovary | becomes the fruit | 69 | |
| 8752191673 | what is the fate of the nucellus | becomes the endosperm and then the cotyledons | 70 | |
| 8752194300 | what is the fate of the polar nuclei | becomes the endosperm | 71 | |
| 8752196260 | what is the fate of the ovary wall | pericarp (fruit wall) | 72 | |
| 8751684293 | what is a fruit | mature ovary that may contain seeds | 73 | |
| 8751684294 | what are fruit formed by/from | from the ovary under the influence of growth regulators (auxins) | 74 | |
| 8751684295 | what are the fuctions of the fruit (2) | protect the seeds and enable seeds to be dispersed | 75 | |
| 8751684296 | 2 examples of dry fruit | pea pods and cereal grains | 76 | |
| 8752218254 | 2 examples of moist fruit | tomatoes and grapes | 77 | |
| 8752226565 | what is parthenocarpy | formation of fruit without a seed, the egg isn't fertilised | 78 | |
| 8752233574 | how are seedless fruits grown | genetically (bananas, pineapples), spraying plants with growth regulators then fruits may form without fertilisation (peppers, cherries) | 79 | |
| 8751684300 | what does the growth regulator ethene do to fruits | ripens them and 'degrees' fruit, e.g. melons and bananas | 80 | |
| 8751684301 | what gas inhibits the production of ethene | carbon dioxide | 81 | |
| 8752263730 | what is dispersal | the transfer of the seed away from the parent plant | 82 | |
| 8752267277 | advantages of dispersal | reduce competition, increases chance of survival, find new areas for growth and increase the number of species | 83 | |
| 8752278612 | 3 examples of wind dispersal | orchid seeds (small and blown far), ash (fruit with wings), dandelions (parachute devices, disperse seeds more widely) | 84 | |
| 8752287945 | 2 examples of water dispersal | coconut trees and water lilies (light, air-filled fruits that float) | 85 | |
| 8752293282 | example of self dispersal | dehiscent fruits (peas, beans) have explosive mechanism that caplets seeds away and when pods dry out they split open | 86 | |
| 8752300062 | 2 examples of animal dispersal | sticky: fruit with hooks attach to animals hair (buttercup). Edible, fleshy, succulent: attract, eaten and digested by animals (strawberry) | 87 | |
| 8752308638 | what is dormancy | resting period when seeds undergo no growth and have reduced metabolism | 88 | |
| 8752316402 | advantages of dormancy | avoid harsh conditions for winter, gives embryo time to develop, allows time for seed dispersal, always some seeds in the soil helps species to survive | 89 | |
| 8752324563 | causes of dormancy | growth inhibitors (abscisic acid), testa impermeable to water, testa too hard, lack of growth regulator | 90 | |
| 8752332938 | germination | the regrowth of the embryo after the dormant period, if environmental conditions are suitable | 91 | |
| 8752358321 | events in germination | leave it | 92 |
Flashcards
World Civilizations, The Global Experience AP, Chapter 19 Flashcards
Terms : Hide Images
| 8413865629 | How was the commercial experience of the Portuguese extended to the Americas? | The Portuguese experience in Africa and their involvement in slave trading was extended to the Americas | 0 | |
| 8413865630 | The grants of Indians to individual Spaniards as a labor system were called | Encomiendas | 1 | |
| 8413865631 | How did the Caribbean cities differ from those of Europe | American cities were laid out in a grid plan | 2 | |
| 8413865632 | What are some of the advantages that the Spanish had over the Indians | Epidemic disease weakened the Indians, use of firearms and steel weapons, rivalries and use of horses | 3 | |
| 8413865633 | What accounted for the majority of the population loss suffered by Native Americans after the European arrival? | Epidemic diseases | 4 | |
| 8413865634 | The tremendous decline of the Indian population in Mexico was matched by the rapid increase in what Colombian exchange item | European livestock | 5 | |
| 8413865635 | Why were the encomiendas discontinued by the 1620s | The Spanish crown did not want to see the growth of a new nobility and the decline of the Indian population made them less attractive | 6 | |
| 8413865636 | How would you describe the nature of the economy in Spanish America | Many engaged in agriculture, but the Spanish commercial system was organized around the mining economy | 7 | |
| 8413865637 | Why was the discovery of mercury in Peru critical to the colonial economy | Mercury was indispensable to the extraction of silver from ore-bearing rock. | 8 | |
| 8413865638 | In what way did the importation of American bullion negatively affect the Spanish economy | The arrival of American treasure contributed to a sharp rise in prices and a general inflation | 9 | |
| 8413865639 | The Treaty of Tordesillas of 1494 divided the world into spheres of influence belonging to what two nations | Portugal and Spain | 10 | |
| 8413865640 | What was introduced by the Catholic church within the Americas? | Universities, baroque churches, establishing missions and monasteries | 11 | |
| 8413865641 | What was the major difference between the Spanish and Portuguese empires (location of colonies) | Unlike the Spanish empire that was almost exclusively America, the Portuguese empire included colonies and outposts in Asia and Africa as well as Brazil | 12 | |
| 8413865642 | What conditions undercut the position of the Brazilian sugar plantation economy? | Competition from English, French and Dutch plantation colonies in the Caribbean led to rising prices for slaves and falling prices for sugar | 13 | |
| 8413865643 | What was the negative impact of the discover of gold on Portugal? | Portugal failed to develop internal industries because the supply of gold allowed the Portuguese to purchase manufactured goods from other European countries | 14 | |
| 8413865644 | What was the impact of the 18th century reforms on slavery in Brazil | Brazil remained as profoundly based on slavery in the late 18th century as it had ever been | 15 |
Unit 1 AP Pysch Flashcards
Terms : Hide Images
| 10525671249 | Pyschology | the scientific study of behavior and mental processes - A friend looks sad and they tell you what they are feeling which tries to make you understand their mental process | 0 | |
| 10525696648 | Introspection | examination of one's own thoughts and feelings - meditate to understand your feelings | 1 | |
| 10525701668 | Structuralism | That uses introspection to explore the elemental structure of the human mind - A rock is rough, hard, dark, big | 2 | |
| 10525721787 | Functionalism | Focuses on how mental and behavioral processes function- and how we adapt, survive, and flourish. - Functions of consciousness - In school we adapt to our teachers and classes and study to survive and we flourish with getting good grades and understanding | 3 | |
| 10525741921 | Evolutionary Psychology | the attempt to explain social behavior in terms of genetic factors that have evolved over time according to the principles of natural selection - biology and experience - Phobias- being scared of spiders and snakes more than lions and tigers | 4 | |
| 10536517785 | Psychoanalytic Perspective | Behavior results from unconscious mind/drives ( unconscious mind is repressed negative childhood memories) - Kara had a abusive dad when growing up and her relationship with her bf is abusive | 5 | |
| 10536518489 | Behaviorism | behavior can be in terms in conditioning, observable behaviors - a teacher gives the students a treat at the end of the week for good behavior | 6 | |
| 10536519220 | Humanistic Perspective | knowing ones self and positive self growth love and acceptance - if not happy or is bored with life, do some soul searching and find what is missing. Friendship?Hobbies? | 7 | |
| 10536520583 | Cognitive Perspective | study of mental processes- thinking, feeling, remembering, and learning - Doing math problems and remembering how to solve and understand the problem | 8 | |
| 10536522173 | Neuroscience/Bio psychology Perspective | how the body and brain enables emotions, memories, and sensory experiences - body chemistry or neurotransmitters - drinking, eating, reading, speaking, results in neural activity and causes behavior | 9 | |
| 10536522982 | Socio-Cultural Perspective | how our thoughts and behaviors vary from people living in other cultures - going to church and believing your religion affects how your behavior is | 10 | |
| 10536524599 | Psychologist | A scientist who studies the mind and behavior of humans and animals - Carl Rogers was a humanistic psychologists and dealt with how people can be the best they can be | 11 | |
| 10536525331 | Psychiatrist | medical doctor who has specialized in treating psychological disorders and prescribes medicine - Sigmund Freud created psychotherapy and was a professor in medicine | 12 | |
| 10536525686 | Clinical Psychologists | studies and treats people w/ psychological problems - Depression, Anxiety, Eating Disorders - B.F Skinner | 13 | |
| 10536526371 | Counseling Psychologists | assists people with problems in living and in achieving greater well-being - marriage, school, home | 14 | |
| 10536528514 | Community Psychologist | study individuals in their environment and how institutions affect individuals - The Black Lives Matter movement started and spread they would try to work to make people feel equal and try to build a better relationship between cops and people. | 15 | |
| 10536529793 | Industrial/Organizational Psychologists | aim to improve productivity and the quality of work life by applying psychological principles and methods to the workplace - IO Psychologist going into a company and talk about leadership and employee motivation | 16 | |
| 10536530865 | Developmental Psychologist | a psychologist who studies the emotional, cognitive, biological, personal, and social changes that occur as an individual matures - work with people that have disabilities, elderly, homeless | 17 | |
| 10536530868 | Plato | Founded an academy in Athens, he and Socrates believed in the mind is separate from the body and that knowledge is innate (born with us). (student of Socrates) | 18 | |
| 10536532400 | Socrates | Founder of Western Philosophy and believed in the love of wisdom was a holy quest or sacred path | 19 | |
| 10536533139 | Descartes | first modern philosopher connected geometry and algebra together to solve geometrical problems "I think therefore I am" | 20 | |
| 10536534043 | Francis Bacon | came up with the scientific method by challenging Aristotelian ideas | 21 | |
| 10536535520 | Wilhelm Wundt | founder of structuralism and worked on introspection.Involved in the 1st psych lab in the world | 22 | |
| 10536536674 | William James | founder of functionalism; studied how humans use perception to function in our environment | 23 | |
| 10536537213 | Max Wertheimer | began Gestalt Psych, worked in experimental psychology and the study of sensation and perception. | 24 | |
| 10536538185 | Mary Whiton Calkins | conducted research on memory, personality, and dreams; first woman president of the American Psychological Association (rejected her doctorate degree) | 25 | |
| 10536538579 | Maragret Floy Washburn | did experimental work in animal behavior and motor theory development. First woman to earn a doctoral degree in American Psych and 2nd APA President | 26 | |
| 10536539334 | G. Stanley Hall | focused on childhood development and evolutionary theory (1st for earning a PhD and the president of APA) | 27 | |
| 10536541724 | Sigmund Freud | founded psychoanalysis, worked on unconscious behavior, and id,ego,superego | 28 | |
| 10536542121 | John Waston | Behaviorism (started the school of behaviorism) "Psychology as the Behaviorist Views It." helped understand his theory of behavior | 29 | |
| 10536542122 | Ivan Pavlov | known for classical conditioning of dogs and his field was in Gastroenterology | 30 | |
| 10536542946 | B.F Skinner | Behaviorism (operant conditioning)- learning is learned through rewards and consequences | 31 | |
| 10536544498 | Jean Piaget | Cognition- came up with the 4 stages of cognitive development from birth to language | 32 | |
| 10536545140 | Abraham Maslow | Humanistic psychologist known for his "Hierarchy of Needs" and the concept of "self-actualization" | 33 | |
| 10536545141 | Carls Rogers | Humanistic- came up with client-centered therapy that helps bring out their full self and potential | 34 | |
| 10536545735 | Charles Darwin | famous for the theory of evolution and wrote "The Origin of Species" which is the basics of evolutionary studies | 35 |
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