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Unit 2 AP Psychology

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Psychology
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Causal inference
Design of experiments
Knowledge
Metaphysics
Scientific method
Psychometrics
Covariance and correlation
Experiments
Confounding
Statistics
Descriptive statistics
Correlation coefficient

UNIT 2 NOTES: Research Methods The Need for Psychological Science Critical Thinking thinking that does not blindly accept arguments and conclusions examines assumptions discerns hidden values evaluates evidence Three hurdles that tend to skew our logic: Hindsight Bias The tendency to believe, after learning the outcome, that you knew it all along Overconfidence We tend to think we know more than we do The Barnum Effect It is the tendency for people to accept very general or vague characterizations of themselves and take them to be accurate Applied V. Basic Research Applied Research has clear, practical applications. Basic Research explores questions that you may be curious about, but not intended to be immediately used The Scientific Method Theory

Statistics (Myers)

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Psychology
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Descriptive statistics
Data analysis
Summary statistics
Statistics
Central tendency
Deviation
Statistical dispersion
Standard deviation
Frequency distribution
Normal distribution
Median
Mean

AP Psychology Statistics Unit 2: Statistics Reading Questions Module 7: pages 56-61 What is ?the point to remember? about statistics? The point to remember about statistics is doubt big, round, and undocumented numbers. What are descriptive statistics? Descriptive statistics is the numerical data used to measure and describe characteristics of groups; includes measures of central tendency and measures of variation. What is the ?fancy? name for a bar graph? A histogram is a bar graph depicting a frequency distribution. What is meant by measure of central tendency? A measure of central tendency is a single score that represents a whole set of scores. Define mode, median & mean. Mode: the most frequently occurring score(s) in a distribution

Hypothesis Testing

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Statistics
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Statistical hypothesis testing
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Scientific method
Null hypothesis
P-value
Null distribution
Statistical significance
Alternative hypothesis
Statistics
Type I and type II errors
F-test
Test statistic

6-1 Section 6: Introduction to Hypothesis Testing To begin with, recall the ?Helper/Hinderer? study that we looked at on the first day of class: Case Study: Naughty or Nice? We all recognize the difference between naughty and nice, right? What about children less than a year old ? do they recognize the difference and show a preference for nice over naughty? In a study reported in the November 2007 issue of Nature, researchers investigated whether infants take into account an individual?s actions towards others in evaluating that individual as appealing or aversive, perhaps laying for the foundation for social interaction (Hamlin, Wynn, and Bloom, 2007). In one component of the study, 10-month-old

AP Stats ch A Variance Analysis

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Statistics
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Descriptive statistics
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Statistical tests
Parametric statistics
Analysis of variance
Design of experiments
Normal distribution
F-test
Student's t-test
Variance
One-way analysis of variance

Chapter Number and Title 813 Post-Exam Topic Analysis of Variance chap15.2EY 7/31/02 2:41 PM Page 813 A 814 Chapter Number and Title W. EDWARDS DEMING Statistics in the Service of Quality From one point of view, statistics is about understanding variation. Reducing variation in products and processes is the central theme of statistical quality control. So it is not surprising that a statistician should become the leading guru of quality management. In the final decades of his long life, W. Edwards Deming (1900?1993) was one of the world?s most influential con- sultants to management. Deming grew up in Wyoming and earned a doctorate in physics at Yale. Working for the U.S. Department of Agriculture in the 1930s, he became

Ch 14.2 Chi square part 3 notes

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Statistics
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Probability and statistics
Normal distribution
Statistical tests
Nonparametric statistics
Pearson's chi-squared test
Chi-squared test
P-value
Chi-squared distribution
Categorical variable
Z-test

Chi-Square Test of Indep. - for problems with 2 categorical variables measured across a single population Ex: How does the presence of an exclusive-territory clause in the contract of a business relate to its survival? A study collected data from a sample of 170 franchise firms. (Note: A firm?s contract may or may not contain the entrepreneur?s right to an exclusive territory. This means the new outlet will be the only representative of the franchise in a specified territory and won?t have to compete with other outlets of the same chain.)

ch 14.2 notes part 3 chi square

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Statistics
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Statistics
Statistical hypothesis testing
Probability and statistics
Normal distribution
Statistical tests
Nonparametric statistics
Pearson's chi-squared test
Chi-squared test
P-value
Chi-squared distribution
Categorical variable
Z-test

Chi-Square Test of Indep. - for problems with 2 categorical variables measured across a single population Ex: How does the presence of an exclusive-territory clause in the contract of a business relate to its survival? A study collected data from a sample of 170 franchise firms. (Note: A firm?s contract may or may not contain the entrepreneur?s right to an exclusive territory. This means the new outlet will be the only representative of the franchise in a specified territory and won?t have to compete with other outlets of the same chain.)

Chapter 11 Test written for Practice of Statistics (Yates, Starnes and Moore) 4th edition

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Statistics
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Statistical hypothesis testing
P-value
Null hypothesis
Student's t-test
Goodness of fit
F-test

Honors Statistics: Chapter 11 Test name___________________ Multiple Choice 1. From experience, the owner of an ice-cream shop has found that 60% of all sales of ice-cream cones are for one-scoop cones, 30% are for two-scoop cones, and the remaining 10% are for three-scoop cones. Recently, the shop added frozen-yogurt cones to its menu. A random sample of 250 sales of frozen-yogurt cones revealed the following distribution: The owner wishes to know whether the pattern of sales for frozen-yogurt cones differs from that of ice-cream cones. In a goodness-of-fit test based on the ?2 distribution, the expected count for "number of two-scoop frozen-yogurt cone sales" would be A. 84. B. 75. C. 83.33.

Ch 12 Test written for Practice of Statistic (Starnes,Yatess and Moore) 4th ed.

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Statistics
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Plot
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Errors and residuals in statistics
Outline of regression analysis
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#AP Statistics

Chapter 12 Test name_________________ Honors Statistics 1. Which of the following would provide evidence that inference procedures for linear regression would be safe to use?? ?A. The scatterplot of the original data displays a nonlinear relationship between the explanatory variable and the response variable. ?B. A scatterplot of the residuals against the values of the explanatory variable displays a random scattering of points about the regression line, with roughly constant variation about the line as we move from left to right. ?C. A stem-and-leaf plot of the residuals displays a clearly skewed distribution. For questions 2-4

Chapter 19 Powerpoint Outline

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Statistics
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Statistical inference
Data analysis
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Statistical theory
Hypothesis testing
Confidence interval
Sampling distribution
Standard deviation
Statistical power
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AP Stats

Stats: Modeling the World Chapter 19 Confidence Intervals for Proportions Making an educated guess? Rarely do we actually know information about our population. Usually we: - take a sample - find a sample statistic - make a guess about the true parameter value Our guess will be a bit off, this is the idea of a confidence interval. The sample proportion ? Recall from Chapter 18 that the sampling distribution model of ? is centered at p, with standard deviation . Since we don?t know p, we can?t find the true standard deviation of the sampling distribution model, so we need to find the standard error: The Empirical Rule Revisited? By the 68-95-99.7% Rule, we know - about 68% of all samples will have ? ?s within 1 SE of p

Chapter 19 Answer Key

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Statistics
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Measurement
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Confidence interval
Econometrics
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Margin of error
Normal distribution
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AP Stats

Chapter 19 Confidence Intervals for Proportions 339 Chapter 19 ? Confidence Intervals for Proportions 1. Margin of error. He believes the true proportion of voters with a certain opinion is within 4% of his estimate, with some degree of confidence, perhaps 95% confidence. 2. Margin of error. He believes the true percentage of children who are exposed to lead-base paint is within 3% of his estimate, with some degree of confidence, perhaps 95% confidence. 3. Conditions. a) Population ? all cars; sample ? 134 cars actually stopped at the checkpoint; p ? proportion of all cars with safety problems; p? ? proportion of cars in the sample that actually have safety problems (10.4%). Plausible Independence condition: There is no reason to believe that the safety problems

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