AP English Literature and Composition Vocabulary Week 13 Flashcards
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| 13526446014 | Vilify | (v.) to abuse or belittle unjustly or maliciously | 0 | |
| 13526446015 | Blandishment | (n.) a flattering or pleasing statement or action used to persuade someone gently to do something | 1 | |
| 13526448976 | Verdant | (adj.) green with grass or other rich vegetation | 2 | |
| 13526448977 | Surfeit | (n.) an excessive amount of something | 3 | |
| 13526453430 | Teem | (v.) pour down; fall heavily | 4 | |
| 13526453431 | Bilateral | (adj.) having or relating to two sides; affecting both sides | 5 | |
| 13526457881 | Capricious | (adj.) given to sudden and unaccountable changes of mood or behavior | 6 | |
| 13526457882 | Extant | (adj.) still in existence; surviving | 7 | |
| 13526461499 | Effervescent | (adj.) vivacious and enthusiastic | 8 | |
| 13526461500 | Transpire | (v.) occur, happen | 9 | |
| 13526465439 | Divest | (v.) deprive (someone) of power, rights, or possessions | 10 | |
| 13526465440 | Deduce | (v.) arrive at a fact or conclusion by reasoning; draw as a logical conclusion | 11 | |
| 13526473107 | Felicitous | (adj.) well chosen or suited to the circumstances | 12 | |
| 13526478253 | Heterogeneous | (adj.) diverse in character or content | 13 | |
| 13526478254 | Abjure | (v.) solemnly renounce | 14 | |
| 13526482111 | Fortuitous | (adj.) happening by accident or chance rather than design | 15 | |
| 13526482112 | Credulous | (adj.) having or showing too great a readiness to believe things | 16 | |
| 13526504211 | Immolate | (v.) kill or offer as a sacrifice, especially by burning | 17 | |
| 13526504212 | Meander | (v.) wander at random | 18 | |
| 13526507257 | Auspices | (n.) a divine or prophetic token | 19 | |
| 13526507258 | Inveigh | (v.) speak or write about (something) with great hostility | 20 | |
| 13526510468 | Heresy | (n.) opinion profoundly at odds with what is generally accepted | 21 | |
| 13526513107 | Litigate | (v.) take to a court of law | 22 | |
| 13526513108 | Legacy | (n.) a thing handed down by a predecessor | 23 | |
| 13526517016 | Monolithic | (adj.) very large and characterless | 24 |
Flashcards
AP gov Flashcards
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| 13485971477 | Westboro Baptist Church | "God hates fags" sign held up at Matthew Shepard's (subject of the Laramie Project) funeral, went to court for emotional harm, but they lost. They protest the Laramie Project and are known for hate speech. | 0 | |
| 13485976831 | Schenck v. United States (1919) | Clear and present danger test by Supreme court to distinguish between protected/unprotected speech. -examines if danger will bring about substantive evils | 1 | |
| 13486043777 | Marbury v. Madison (1803) | Adams appointed judges whose commissions were not honored by Jefferson -ruled: Established Judicial Review, the ability for courts to interpret the Constitution | 2 | |
| 13486049436 | Frederick v Morse | student held up sign "Bong hits for Jesus." school claimed that it was a field trip and that academic propriety was violated. Ruled in favor of school bc his sign promoted illegal drug use on campus against their policy. | 3 | |
| 13486069686 | Brown v. Board of Education 1954 | The Supreme Court overruled Plessy v. Ferguson, declared that racially segregated facilities are inherently unequal and ordered all public schools desegregated. -overturned Separate but Equal standard of discrimination in education. | 4 | |
| 13486081594 | Gideon v. Wainwright (1963) | Extends to the defendant the right of counsel in all state and federal criminal trials regardless of their ability to pay. -6th am. | 5 | |
| 13486087819 | Shaw v. Reno (1993) | NO racial gerrymandering; race cannot be the sole or predominant factor in redrawing legislative boundaries; majority-minority districts. -North Carolina, 14th amendment equal protection clause | 6 | |
| 13486115478 | McDonald v. Chicago (2010) | sued Chicago and Oat Park Illinois challenging gun ban, in District of Columbia v Heller - 2nd amendment should also apply to the states. | 7 | |
| 13486158853 | Tinker v. Des Moines (1969) | Public school students may wear armbands to class protesting against America's war in Vietnam when such display does not disrupt classes | 8 | |
| 13486160365 | McCulloch v. Maryland (1819) | the Supreme Court upheld the power of the national government and denied the right of a state to tax the federal bank using the Constitution's supremacy clause. The Court's broad interpretation of the necessary and proper clause paved the way for later rulings upholding expansive federal powers | 9 | |
| 13486164784 | U.S. v. Lopez (1995) | Gun Free School Zones Act exceeded Congress' authority to regulate interstate commerce. -guilty 6 months in prison | 10 | |
| 13486169064 | Baker v. Carr (1962) | Tennessee citizens argued that law to apparition state's general assembly was disregarded | 11 | |
| 13486185008 | Wisconsin v. Yoder (1972) | Amish children do not have to go to school until they are 16---they may stop after the 8th grade | 12 | |
| 13486208105 | New York Times v. US | Nixon tried to prevent Pentagon papers about Vietnam top secrets | 13 | |
| 13486213070 | Engle v. Vitale (1962) | Penn, RI taxpayer $ used to fund religious private schools. violated the first amendment (interfered with the separation of church and state) | 14 | |
| 13486220746 | Citizens United v. FEC | political group sought injunction against Federal Elections Commission in the USDC for District of Columbia to prevent application of Bipartisan Campaign Reform Act to its film Hillary | 15 | |
| 13486252973 | Griswold v. Connecticut (1965) | banned the use of any drug, medical device, or other instrument in furthering contraception. - Constitution protect the right of marital privacy against state restrictions on contraception. | 16 | |
| 13486256357 | Roe v. Wade (1973) | Texas law prohibited abortions except to save the pregnant woman's life. -woman's right to an abortion fell within the right to protected by the Fourteenth Amendment | 17 | |
| 13486259446 | Texas v. Johnson (1989) | Gregory Lee Johnson burned an American flag as a means of protest against Reagan administration policies. - Can states criminalize flag burning? flag burning, "is protected speech because it contains a sufficient level of communication" | 18 | |
| 13486264338 | Lemon v. Kurtzman (1971) | Pennsylvania used government money to fund programs that taught religious lessons, programs, and studies to private schools, under the Non-Public Elementary School Act Did state assistance to private, religious schools violate the Establishment Clause, BUT does withholding federal money to religious schools violate the Exercise Clause? -Yes. "There should be no excessive entangled by the government." Sets precedent of policies regarding establishment of religion, referred to as the Lemon Test. | 19 | |
| 13486269956 | Lemon Test (Lemon v. Kurtzman) | Three tests are described for deciding whether the government is improperly involved with religion. 1) Has a secular purpose. 2) Its primary effect neither advances nor inhibits religion. 3) It does not foster an excessive government entanglement with religion. | 20 | |
| 13486276838 | Civil Liberties | individual rights that protect people against the government | 21 | |
| 13486280648 | incorporation doctrine | The legal concept under which the Supreme Court has nationalized the Bill of Rights by making most of its provisions applicable to the states through the Fourteenth Amendment. | 22 | |
| 13486288124 | RAPPS | Religion, Assembly, Press, Petition, Speech | 23 | |
| 13486289307 | Free Exercise Clause | The government cannot restrict your rights to practice a specific religion | 24 | |
| 13486291245 | Establishment Clause | The government cannot establish a national religion | 25 | |
| 13486299592 | clear and present danger test | law should not punish speech unless there was a clear and present danger of producing harmful actions | 26 | |
| 13486300956 | National Security | the ability to keep the country safe from attack or harm Threatens our ability to fight war Publishing national secrets | 27 | |
| 13486305000 | obscene speech | Depicts sexual conduct in a manner that is "patently offensive" to community standards, and lacks serious artistic, political, or scientific value sexual acts (porn) | 28 | |
| 13486308664 | Freedom of Speech on television | Can be regulated by the government Especially on major networks FCC | 29 | |
| 13486311741 | symbolic speech | nonverbal communication, such as burning a flag or wearing an armband. The Supreme Court has accorded some symbolic speech protection under the first amendment. | 30 | |
| 13486312729 | freedom of the press | the right of journalists to publish the truth without restriction or penalty | 31 | |
| 13486313317 | Libel | A written defamation of a person's character, reputation, business, or property rights. | 32 | |
| 13486314532 | Slander | the action or crime of making a false spoken statement damaging to a person's reputation. | 33 | |
| 13486316459 | Can the press influence a fair trial? | Too much press can influence the jury Ohio rape case | 34 | |
| 13486320200 | Freedom of assembly | the right of the people to gather peacefully and to petition government | 35 | |
| 13486330703 | hate groups | organizations that promote hostility or violence toward others based on race and other factors | 36 | |
| 13486349469 | Three levels of courts | U.S. District Court U.S. Circuit Courts of Appeals Supreme Court | 37 | |
| 13486351289 | Judges/justices: | Appointed by President Serve for life | 38 | |
| 13486353403 | Original jurisdiction and appellate jurisdiction | The original jurisdiction of a court is the power to hear a case for the first time, as opposed to appellate jurisdiction, when a court has the power to review a lower court's decision. | 39 | |
| 13486354360 | Organization Of The Federal Court System |  | 40 | |
| 13486356449 | Article III | Federalist #78written by Alexander Hamilton; talks about the federal judiciary; judiciary must depend on other two branches to uphold its decisions Weak Not meant to determine law Treason-Only crime mentioned in Constitution 2 witnesses Death | 41 | |
| 13486358246 | Judiciary Act of 1789 | Established the constitutional courts Three tiers: District courts Circuit courts 6 SCOTUS justices | 42 | |
| 13486359190 | U.S. District Courts | Trial courts created by Congress 94 districts Nearly 700 justices Hear criminal and civil matters -Plaintiff v. defendant Fact finders Federal Crimes Most fall under Article I, Section 8 Right to a jury Right to defense lawyer Plea bargain U.S. Attorneys Each district has own - appointed by POTUS Attorney General Civil Cases Torts Class action suits Suing the Government Sovereign immunity Happens a lot Special Legislative Courts Created by Congress Judges - 15 year terms Specialized | 43 | |
| 13486364123 | U.S. Circuit Courts | Created by Congress 11 regional courts 2 courts in D.C. Nearly 200 justices Takes appeals from district courts Justices sit in panels of 3 | 44 | |
| 13486375845 | U.S. Circuit Court of Appeals | Appellate Jurisdiction Now permanent Don't determine facts - help shape the law Certiorari Panels of 3 judges Petitioner v. Respondent Do not determine guilt or innocence 11 circuits 200 justices Sit en banc 2 in DC Patents, contracts, financial claims against the US Circuit Court of Appeals - works w/ bureaucracy | 45 | |
| 13486365196 | U.S. Supreme Court | Created by Article III of Constitution 9 justices - 1 chief Hears 80-100 cases from October through June Has original jurisdiction in unique cases Takes appeals from circuits and top state courts | 46 | |
| 13486380757 | History of SCOTUS | John Jay John Marshall Precedents | 47 | |
| 13486381444 | Marshall Court | 7 members Strengthened the nation Judicial Review Marbury v. Madison (1803) McCulloch v. Maryland (1819) Gibbons v. Ogden (1825) Commonality: sided w/ Congress | 48 | |
| 13486382661 | The Taney Court | Private property & activities of corporations can be regulated by state legislatures Roger Taney 9 justices Slavery Dred Scott v. Sandford (1855) Slaves ≠ citizens | 49 | |
| 13486383500 | Late 1800s | Business, trade, workplace regulations Mostly conservative Strictly constructionist Struck down minimum wage, maximum hours, and child labor laws | 50 | |
| 13486385067 | The New Deal and Roosevelt's Court Packing Plan | Still fairly conservative New building Roosevelt's plan to pack the court Dilute the "nine old men" Attack on the Court's independence Justice Owen Roberts | 51 | |
| 13486387876 | Post WW2 Courts | Protected/extended individual liberties | 52 | |
| 13486388703 | The Warren Court | the chief justice that overturned Plessy v. Ferguson in Brown v. Board of Education (1954); he was the first justice to help the civil rights movement, judicial activism Extension of civil liberties Brown v. Board of Education Overturned Plessy v. Ferguson Miranda v. Arizona Tinker v. Des Moines | 53 | |
| 13486390261 | The Burger Court | a conservative jurist appointed by Nixon that nonetheless continued the judicial activism of the Warren Court as seen by Roe v. Wade; this was due to the other members of the court rather than his own liberal beliefs Continuation of the Warren Court Roe v. Wade | 54 | |
| 13486392590 | William Rehnquist | United States jurist who served as an associate justice on the United States Supreme Court from 1972 until 1986, when he was appointed chief justice (born in 1924) | 55 | |
| 13486393619 | The Rehnquist Court | Reduced court load and improved procedures Upheld states' rights | 56 | |
| 13486394617 | The Roberts Court | Judicial minimalism Hard to predict | 57 | |
| 13486396672 | The Modern Supreme Court | Vacancies infrequent Chief justice vacancy unique Partisan balance in Senate key | 58 | |
| 13486400209 | Accepting Cases | First step in process -10,000 appeals per year -Justices meet in conference -once a week -Rule of four -Writ of certiorari Types of cases selected -Civil liberties -Discrepancies -interpretation of a law -Solicitor general's request | 59 | |
| 13486403651 | Process of Decision Making | Oral arguments -Briefs -Amicus Curiae briefs -30 minutes for each side Opinion writing -Chief justice assigns opinion, if in majority -Explain legal reasoning -Concurring opinion -Dissenting opinion | 60 | |
| 13486406264 | Basis of Decisions | - Vast majority of cases decided on the principle of stare decisis - Why do justices disagree - Ambiguity and vagueness - judicial philosophy - originalism Why do justices disagree? Ambiguity and vagueness Judicial philosophy Originalism/Restraint Activism | 61 | |
| 13486408765 | Virgil Hawkins | the case of a black man named virgil hawkins who tried to get admitted to the university of florida law school illustrates how other courts and other institutions of government can be roadblocks in the way of judicial implementation | 62 | |
| 13486417960 | Judicial implementation | Interpreting population Implementing population Consumer population | 63 | |
| 13486420918 | Criteria for Selection | Geography Religion Ideology/partisanship Senatorial Courtesy | 64 | |
| 13486575545 | Magna Carta | the royal charter of political rights given to rebellious English barons by King John in 1215 | 65 | |
| 13486576488 | Who decides process "due" | Policy makers make rules Judges interpret constitutions (national/state) | 66 | |
| 13486577554 | What are life, liberty, property? | Common sense meanings Broader meanings Life Includes corporations Liberty includes movement and (past) contracts Property includes reputation, job, inventions | 67 | |
| 13486579165 | Due process in practice | Criminal-- Notice, fair trial, counsel, pre and post processes Civil-- Notice, hearing, employ counsel, impartial decision-maker Civil includes administrative actions E.g., termination of benefits, school discipline, licensing/regulation | 68 | |
| 13486580730 | Two additional dimensions of due process | Substantive due process Incorporation of Bill of Rights | 69 | |
| 13486581597 | "SUBSTANTIVE" due process | There are some things governments cannot do at all, no matter what procedures they follow "Fundamental rights" analysis U.S. Supreme Court decides what government cannot do | 70 | |
| 13486582187 | Examples of substantive due process | Late 19th century: Liberty of contract State and national economic regulatory laws struck down 20th century: Right of privacy Laws banning interracial marriage, abortion, and some sexual practices struck down | 71 | |
| 13486583249 | "Incorporation" of Bill of Rights | Bill of Rights limits national government 14th Amendment due process clause limits states Does 14th Amendment due process mean Bill of Rights also limits states? | 72 | |
| 13486583988 | Supreme Court embraces "selective incorporation" | Not all rights in Bill of Rights are equal Due process requires states to respect rights "fundamental to scheme of ordered justice" Whether right in Bill of Rights limits state decided case-by-case | 73 |
AP Statistics Flashcards
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| 13961059062 | 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 | |
| 13961059063 | If a graph is skewed, should we calculate the median or the mean? Why? | median; it is resistant to skews and outliers | 1 | |
| 13961059064 | 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 | |
| 13961059065 | What is in the five number summary? | Minimum, Q1, Median, Q3, Maximum | 3 | |
| 13961059066 | Relationship between variance and standard deviation? | variance=(standard deviation)^2 | 4 | |
| 13961059067 | variance definition | the variance is roughly the average of the squared differences between each observation and the mean | 5 | |
| 13961059068 | standard deviation | the standard deviation is the square root of the variance | 6 | |
| 13961059069 | What should we use to measure spread if the median was calculated? | IQR | 7 | |
| 13961059070 | What should we use to measure spread if the mean was calculated? | standard deviation | 8 | |
| 13961059071 | What is the IQR? How much of the data does it represent? | Q3-Q1; 50% | 9 | |
| 13961059072 | 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 | |
| 13961059253 | What is the formula for standard deviation? |  | 11 | |
| 13961059073 | Categorical variables vs. Quantitative Variables | Categorical: individuals can be assigned to one of several groups or categories Quantitative: takes numberical values | 12 | |
| 13961059074 | If a possible outlier is on the fence, is it an outlier? | No | 13 | |
| 13961059075 | 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 | |
| 13961059076 | 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 | |
| 13961059077 | 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 | |
| 13961059078 | 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 | |
| 13961059079 | Inverse Norm | when you want to find the percentile: invNorm (area, mean, standard deviation) | 18 | |
| 13961059080 | z | (x-mean)/standard deviation | 19 | |
| 13961059081 | pth percentile | the value with p percent observations less than is | 20 | |
| 13961059082 | 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 | |
| 13961059083 | 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 | |
| 13961059084 | r | tells us the strength of a LINEAR association. -1 to 1. Not resistant to outliers | 23 | |
| 13961059085 | 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 | |
| 13961059086 | 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 | |
| 13961059087 | 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 | |
| 13961059088 | residual formula | residual=y-y(hat) aka observed y - predicted y | 27 | |
| 13961059089 | 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 | |
| 13961059090 | 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 | |
| 13961059091 | n | number of trials | 30 | |
| 13961059092 | p | probability of success | 31 | |
| 13961059093 | k | number of successes | 32 | |
| 13961059094 | Binomial Formula for P(X=k) | (n choose k) p^k (1-p)^(n-k) | 33 | |
| 13961059095 | Binomial Calculator Function to find P(X=k) | binompdf(n,p,k) | 34 | |
| 13961059096 | Binomial Calculator Function for P(X≤k) | binomcdf(n,p,k) | 35 | |
| 13961059097 | Binomial Calculator Function for P(X≥k) | 1-binomcdf(n,p,k-1) | 36 | |
| 13961059098 | mean of a binomial distribution | np | 37 | |
| 13961059099 | standard deviation of a binomial distribution | √(np(1-p)) | 38 | |
| 13961059100 | Geometric Formula for P(X=k) | (1-p)^(k-1) x p | 39 | |
| 13961059101 | Geometric Calculator Function to find P(X=k) | geometpdf(p,k) | 40 | |
| 13961059102 | Geometric Calculator Function for P(X≤k) | geometcdf(p,k) | 41 | |
| 13961059103 | Geometric Calculator Function for P(X≥k) | 1-geometcdf(p,k-1) | 42 | |
| 13961059104 | Mean of a geometric distribution | 1/p=expected number of trials until success | 43 | |
| 13961059105 | Standard deviation of a geometric distribution | √((1-p)/(p²)) | 44 | |
| 13961059106 | 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 | |
| 13961059107 | how do you enter n choose k into the calculator? | type "n" on home screen, go to MATH --> PRB --> 3: ncr, type "k" | 46 | |
| 13961059108 | μ(x+y) | μx+μy | 47 | |
| 13961059109 | μ(x-y) | μx-μy | 48 | |
| 13961059110 | σ(x+y) | √(σ²x+σ²y) | 49 | |
| 13961059111 | 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 | |
| 13961059112 | 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 | |
| 13961059113 | 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 | |
| 13961059114 | calculate μx by hand | X1P1+X2P2+.... XKPK (SigmaXKPK) | 53 | |
| 13961059115 | calculate var(x) by hand | (X1-μx)²p(1)+(X2-μx)²p(2)+.... (Sigma(Xk-μx)²p(k)) | 54 | |
| 13961059116 | Standard deviation | square root of variance | 55 | |
| 13961059117 | discrete random variables | a fixed set of possible x values (whole numbers) | 56 | |
| 13961059118 | 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 | |
| 13961059119 | 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 | |
| 13961059120 | mutually exclusive | no outcomes in common | 59 | |
| 13961059121 | addition rule for mutually exclusive events P (A U B) | P(A)+P(B) | 60 | |
| 13961059122 | complement rule P(A^C) | 1-P(A) | 61 | |
| 13961059123 | general addition rule (not mutually exclusive) P(A U B) | P(A)+P(B)-P(A n B) | 62 | |
| 13961059124 | intersection P(A n B) | both A and B will occur | 63 | |
| 13961059125 | conditional probability P (A | B) | P(A n B) / P(B) | 64 | |
| 13961059126 | independent events (how to check independence) | P(A) = P(A|B) P(B)= P(B|A) | 65 | |
| 13961059127 | multiplication rule for independent events P(A n B) | P(A) x P(B) | 66 | |
| 13961059128 | general multiplication rule (non-independent events) P(A n B) | P(A) x P(B|A) | 67 | |
| 13961059129 | sample space | a list of possible outcomes | 68 | |
| 13961059130 | probability model | a description of some chance process that consists of 2 parts: a sample space S and a probability for each outcome | 69 | |
| 13961059131 | event | any collection of outcomes from some chance process, designated by a capital letter (an event is a subset of the sample space) | 70 | |
| 13961059132 | 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 | |
| 13961059133 | Complement | probability that an event does not occur | 72 | |
| 13961059134 | What is the sum of the probabilities of all possible outcomes? | 1 | 73 | |
| 13961059135 | What is the probability of two mutually exclusive events? | P(A U B)= P(A)+P(B) | 74 | |
| 13961059136 | 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 | |
| 13961059137 | When is a two-way table helpful | displays the sample space for probabilities involving two events more clearly | 76 | |
| 13961059138 | In statistics, what is meant by the word "or"? | could have either event or both | 77 | |
| 13961059139 | When can a Venn Diagram be helpful? | visually represents the probabilities of not mutually exclusive events | 78 | |
| 13961059140 | 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 | |
| 13961059141 | What does the intersection of two or more events mean? | both event A and event B occur | 80 | |
| 13961059142 | What does the union of two or more events mean? | either event A or event B (or both) occurs | 81 | |
| 13961059143 | 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 | |
| 13961059144 | 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 | |
| 13961059145 | How do you interpret a probability? | We interpret probability to represent the most accurate results if we did an infinite amount of trials | 84 | |
| 13961059146 | 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 | |
| 13961059147 | simulation | the imitation of chance behavior, based on a model that accurately reflects the situation | 86 | |
| 13961059148 | 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 | |
| 13961059149 | 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 | |
| 13961059150 | What does the intersection of two or more events mean? | both event A and event B occur | 89 | |
| 13961059151 | 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 | |
| 13961059152 | population | In a statistical study, this is the entire group of individuals about which we want information | 91 | |
| 13961059153 | 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 | |
| 13961059154 | convenience sample | A sample selected by taking the members of the population that are easiest to reach; particularly prone to large bias. | 93 | |
| 13961059155 | bias | The design of a statistical study shows ______ if it systematically favors certain outcomes. | 94 | |
| 13961059156 | voluntary response sample | People decide whether to join a sample based on an open invitation; particularly prone to large bias. | 95 | |
| 13961059157 | random sampling | The use of chance to select a sample; is the central principle of statistical sampling. | 96 | |
| 13961059158 | simple random sample (SRS) | every set of n individuals has an equal chance to be the sample actually selected | 97 | |
| 13961059159 | strata | Groups of individuals in a population that are similar in some way that might affect their responses. | 98 | |
| 13961059160 | 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 | |
| 13961059161 | 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 | |
| 13961059162 | inference | Drawing conclusions that go beyond the data at hand. | 101 | |
| 13961059163 | margin of error | Tells how close the estimate tends to be to the unknown parameter in repeated random sampling. | 102 | |
| 13961059164 | sampling frame | The list from which a sample is actually chosen. | 103 | |
| 13961059165 | undercoverage | Occurs when some members of the population are left out of the sampling frame; a type of sampling error. | 104 | |
| 13961059166 | nonresponse | Occurs when a selected individual cannot be contacted or refuses to cooperate; an example of a nonsampling error. | 105 | |
| 13961059167 | 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 | |
| 13961059168 | observational study | Observes individuals and measures variables of interest but does not attempt to influence the responses. | 107 | |
| 13961059169 | experiment | Deliberately imposes some treatment on individuals to measure their responses. | 108 | |
| 13961059170 | explanatory variable | A variable that helps explain or influences changes in a response variable. | 109 | |
| 13961059171 | response variable | A variable that measures an outcome of a study. | 110 | |
| 13961059172 | lurking variable | a variable that is not among the explanatory or response variables in a study but that may influence the response variable. | 111 | |
| 13961059173 | 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 | |
| 13961059174 | experimental unit | the smallest collection of individuals to which treatments are applied. | 113 | |
| 13961059175 | subjects | Experimental units that are human beings. | 114 | |
| 13961059176 | factors | the explanatory variables in an experiment are often called this | 115 | |
| 13961059177 | 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 | |
| 13961059178 | 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 | |
| 13961059179 | 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 | |
| 13961059180 | 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 | |
| 13961059181 | placebo | an inactive (fake) treatment | 120 | |
| 13961059182 | placebo effect | Describes the fact that some subjects respond favorably to any treatment, even an inactive one | 121 | |
| 13961059183 | 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 | |
| 13961059184 | 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 | |
| 13961059185 | 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 | |
| 13961059186 | 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 | |
| 13961059187 | 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 | |
| 13961059188 | 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 | |
| 13961059189 | simulation | a model of random events | 128 | |
| 13961059190 | census | a sample that includes the entire population | 129 | |
| 13961059191 | population parameter | a number that measures a characteristic of a population | 130 | |
| 13961059192 | systematic sample | every fifth individual, for example, is chosen | 131 | |
| 13961059193 | multistage sample | a sampling design where several sampling methods are combined | 132 | |
| 13961059194 | sampling variability | the naturally occurring variability found in samples | 133 | |
| 13961059195 | levels | the values that the experimenter used for a factor | 134 | |
| 13961059196 | the four principles of experimental design | control, randomization, replication, and blocking | 135 | |
| 13961059197 | completely randomized design | a design where all experimental units have an equal chance of receiving any treatment | 136 | |
| 13961059198 | 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 | |
| 13961059199 | 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 | |
| 13961059200 | probability of getting a certain p̂1-p̂2 (ex. less than .1) | plug in center and spread into bell curve, find probability | 139 | |
| 13961059201 | Confidence intervals for difference in proportions formula | (p̂1-p̂2) plus or minus z*(√((p1(1-p1)/n1)+(p2(1-p2)/n2)) | 140 | |
| 13961059202 | When do you use t and z test/intervals? | t for mean z for proportions | 141 | |
| 13961059254 | Significance test for difference in proportions | 142 | ||
| 13961059203 | What is a null hypothesis? | What is being claimed. Statistical test designed to assess strength of evidence against null hypothesis. Abbreviated by Ho. | 143 | |
| 13961059204 | What is an alternative hypothesis? | the claim about the population that we are trying to find evidence FOR, abbreviated by Ha | 144 | |
| 13961059205 | When is the alternative hypothesis one-sided? | Ha less than or greater than | 145 | |
| 13961059206 | When is the alternative hypothesis two-sided? | Ha is not equal to | 146 | |
| 13961059207 | 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 | |
| 13961059208 | What is the default significance level? | α=.05 | 148 | |
| 13961059209 | 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 | |
| 13961059210 | p value ≤ α | We reject our null hypothesis. There is sufficient evidence to say that (Ha) is true. | 150 | |
| 13961059211 | p value ≥ α | We fail to reject our null hypothesis. There is insufficient evidence to say that (Ho) is not true. | 151 | |
| 13961059212 | reject Ho when it is actually true | Type I Error | 152 | |
| 13961059213 | fail to reject Ho when it is actually false | Type II Error | 153 | |
| 13961059214 | Power definition | probability of rejecting Ho when it is false | 154 | |
| 13961059215 | probability of Type I Error | α | 155 | |
| 13961059216 | probability of Type II Error | 1-power | 156 | |
| 13961059217 | two ways to increase power | increase sample size/significance level α | 157 | |
| 13961059218 | 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 | |
| 13961059255 | Formula for test statistic (μ) |  | 159 | |
| 13961059219 | Formula for test statistic (p̂) (where p represents the null) | (p̂-p)/(√((p)(1-p))/n) | 160 | |
| 13961059220 | probability of a Type II Error? | overlap normal distribution for null and true. Find rejection line. Use normalcdf | 161 | |
| 13961059221 | when do you use z tests? | for proportions | 162 | |
| 13961059222 | when do you use t tests? | for mean (population standard deviation unknown) | 163 | |
| 13961059224 | 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 | 164 | |
| 13961059225 | 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 | 165 | |
| 13961059226 | When doing a paired t-test, to check normality, what do you do? | check the differences histogram (μ1-μ2) | 166 | |
| 13961059227 | 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). | 167 | |
| 13961059228 | How to interpret a C% Confidence Interval | We are C% confident that the interval (_,_) will capture the true parameter (in context). | 168 | |
| 13961059229 | What conditions must be checked before constructing a confidence interval? | random, normal, independent | 169 | |
| 13961059230 | 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). | 170 | |
| 13961059256 | What's the z interval standard error formula? |  | 171 | |
| 13961059231 | How do you find z*? | InvNorm(#) | 172 | |
| 13961059232 | 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) | 173 | |
| 13961059233 | 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 | 174 | |
| 13961059234 | 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 | 175 | |
| 13961059235 | Finding the confidence interval when the standard deviation of the population is *known* | x bar +/- z*(σ/√n) | 176 | |
| 13961059236 | Checking normal condition for z* (population standard deviation known) | starts normal or CLT | 177 | |
| 13961059237 | Finding the confidence interval when the standard deviation of the population is *unknown* (which is almost always true) | x bar +/- t*(Sx/√n) | 178 | |
| 13961059238 | degrees of freedom | n-1 | 179 | |
| 13961059239 | How do you find t*? | InvT(area to the left, df) | 180 | |
| 13961059240 | 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) | 181 | |
| 13961059241 | a point estimator is a statistic that... | provides an estimate of a population parameter. | 182 | |
| 13961059242 | Explain the two conditions when the margin of error gets smaller. | Confidence level C decreases, sample size n increases | 183 | |
| 13961059243 | 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 | 184 | |
| 13961059244 | Sx and σx: which is which? | Sx is for a sample, σx is for a population | 185 | |
| 13961059245 | How do we know when do use a t* interval instead of a z interval? | you are not given the population standard deviation | 186 | |
| 13961059246 | 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) | 187 | |
| 13961059247 | 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) | 188 | |
| 13961059248 | 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). | 189 | |
| 13961059249 | margin of error formula | z* or t* (standard error) | 190 | |
| 13961059250 | 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 | 191 | |
| 13961059251 | What is it looking for if it asks for the appropriate critical value? | z/t* interval | 192 | |
| 13961059257 | One sample t-interval formula |  | 193 | |
| 13961087623 | one proportion z-interval formula |  | 194 | |
| 13961089649 | two sample t-interval formula |  | 195 | |
| 13961091316 | two proportion z-interval formula |  | 196 | |
| 13961093115 | one sample t-test formula | | 197 | |
| 13961095685 | one proportion z-test formula |  | 198 | |
| 13961097587 | two sample t-test formula |  | 199 | |
| 13961098803 | two proportion z-test formula |  | 200 | |
| 13961101867 | Chi-Squared formula |  | 201 |
AP Biology Summer Vocab Flashcards
Terms : Hide Images
| 14368969354 | abiotic factor | a non-living component of the environment ex: climate, soil, sunlight |  | 0 |
| 14368984746 | biotic factor | living components of an ecosystem ex: plants, micro-organisms, predators | | 1 |
| 14368999079 | resource | a substance or object in the environment required by an organism for normal growth, maintenance, and reproduction ex (plants): sunlight, water, nutrients, space to grow ex (animals): food, water, territory |  | 2 |
| 14369021244 | rain shadow | dry area on the downwind side of a mountain |  | 3 |
| 14369049400 | disturbance | a temporary event that changes a community and alters resource availability ex: storm, fire, flood, tree cutting |  | 4 |
| 14369076800 | terrestrial biome | an area of land with a similar climate that includes similar communities of plants and animals |  | 5 |
| 14369147988 | aquatic biome | includes all aquatic ecosystems on the earth's surface either in a freshwater or marine biome |  | 6 |
| 14369164006 | dispersion patterns | Uniform Dispersion pattern: individuals are evenly spaced Clumped Dispersion pattern: individuals are clustered together Random Dispersion pattern: individuals are randomly arranged |  | 7 |
| 14369192335 | competition | the struggle between organisms or species for the same resource within an environment |  | 8 |
| 14369209103 | niche | the role or position a species or organism has in its environment; includes all of its interaction with the biotic and abiotic factor in the environment |  | 9 |
| 14369269134 | cryptic coloration | type of coloration or marking of an animal that aids in camouflaging in its natural environment ex: stripes on a zebra or tiger or spots on a frog |  | 10 |
| 14369300323 | aposematic coloration | conspicuously recognizable markings of an animal that are to warn potential predators of the nuisance or harm that would come from attacking or eating it |  | 11 |
| 14369362693 | batesian mimicry | a harmless species mimics a harmful one |  | 12 |
| 14369373790 | parasitism | A relationship between two organisms of different species where one benefits and the other is harmed |  | 13 |
| 14369376799 | mutualism | A relationship between two species in which both species benefit |  | 14 |
| 14369380006 | commensalism | A relationship between two organisms in which one organism benefits and the other is unaffected |  | 15 |
| 14369492727 | invasive species | plants and animals that have migrated to places where they are not native | 16 | |
| 14369497936 | keystone species | A species that influences the survival of many other species in an ecosystem |  | 17 |
| 14369648640 | primary succession | occurs in lifeless areas; regions where the soil is incapable of sustaining life | 18 | |
| 14369668295 | secondary succession | a process started by an event that reduces an already established ecosystem to a smaller population of species |  | 19 |
| 14369709669 | disease vector | any agent (person, animal, or microorganism) that carries and transmits an infectious pathogen into another living organism | 20 | |
| 14369714419 | food chain | a hierarchical series of organisms on the next as a source of food | 21 | |
| 14369737531 | primary producers | organisms that can synthesize their own food |  | 22 |
| 14369751164 | primary consumer | organisms that only feed on plants | 23 | |
| 14369754880 | tertiary consumer | organism that eats both producers and consumers; omnivores |  | 24 |
| 14369785937 | decomposers | organisms that break down dead or decaying organisms |  | 25 |
| 14369848409 | biodiversity | variety of life in the world or in a particular habitat or ecosystem |  | 26 |
| 14369856317 | habitat loss | the process where natural habitat is changed or destroyed, making it unable for species that live there to remain in the habitat |  | 27 |
| 14369863938 | habitat fragmentation | Breakup of a habitat into smaller pieces, usually as a result of human activities. |  | 28 |
| 14369889592 | secondary consumer | organisms that eat primary consumers |  | 29 |
Flashcards
Flashcards
Flashcards
AP US Government- Amendments Flashcards
Prep for AP Exam, reviews the amendments and which court cases they apply to.
Terms : Hide Images
| 13734382863 | 1st Amendment | Freedom of religion (Engle v Vital, Lemon v Kurtzman), speech (Johnson v Texas, Black v Virginia, Tinker v Des Moines), press, rights of assembly, and to petition | 0 | |
| 13734382864 | 2nd Amendment | Right to bear arms |  | 1 |
| 13734382866 | 4th Amendment | Search and arrest warrants requires probable cause (Mapp v Ohio) |  | 2 |
| 13734382867 | 5th Amendment | Due process rights in criminal cases. Protects against double jeopardy, self-incrimination, and establishes grand jury proceedings (Miranda v Arizona) | 3 | |
| 13734382868 | 6th Amendment | Rights to a fair and speedy trial with representation by council (Gideon v Wainwright) |  | 4 |
| 13734382870 | 8th Amendment | No excessive bails, fines, or cruel and unusual punishments (Furman v Georgia, Gregg v Georgia) |  | 5 |
| 13734382871 | 9th Amendment | Right retained by the people- right of privacy (Griswald v Connecticut, Roe v Wade, Lawrence v Texas) |  | 6 |
| 13734382872 | 10th Amendment | Powers retained by the states or people |  | 7 |
| 13734382874 | 12th Amendment | Providing for election of President and VP. Establishes the electoral college and the process for electing the VP. |  | 8 |
| 13734382876 | 14th Amendment | Due process of the law. Civil rights. Equal protection of the law. (Federal Government=Guarantor of minority rights, linked to almost every court case involving minorities and civil rights) |  | 9 |
| 13734382877 | 15th Amendment | Suffrage for African Americans |  | 10 |
| 13734382879 | 17th Amendment | Direct election of US Senators |  | 11 |
| 13734382881 | 19th Amendment | Women granted suffrage |  | 12 |
| 13734382884 | 22nd Amendment | Set two-term limit for President |  | 13 |
| 13734382886 | 24th Amendment | Poll tax eliminated |  | 14 |
| 13734382888 | 26th Amendment | Granted suffrage to 18,19, and 20 year olds |  | 15 |
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