AP Psychology Warm Up List 5 guidelines that psychologists should follow when conducting experiments with animals. Then list 5 guidelines that should apply to psychologists when conducting experiments involving humans.

AP Psychology Unit 1: Science of Psychology Essential Task 1-8: Apply basic statistical concepts to explain research findings: - Descriptive Statistics: Central Tendency (mean, median, mode, skewed distributions) Variance ( range, standard deviation, and normal distributions) - Inferential Statistics: Statistical significance (t- test and p-value)

The Science of Psychology Approaches to Psych Growth of Psych Research Methods Statistics DescriptiveCorrelationExperiment Case Study Survey Naturalistic Observation DescriptiveInferential Ethics Sampling Central Tendency Variance Careers We are here

Essential Task 1-: Descriptive Statistics: –Central Tendency Mean, median, and mode skewed distributions –Variance Range standard deviation normal distributions Inferential Statistics: –Statistical significance t-test and the p-valuet-testp-value –Confidence intervalsConfidence intervals Outline

Why is statistical reasoning important? Statistical procedures analyze and interpret data and let us see what the unaided eye misses. Composition of ethnicity in urban locales

Central Tendency Tendency of scores to congregate around some middle variable A measure of central tendency identifies what is average or typical in a data set

Measures of Central Tendency Mode: The most frequently occurring score in a distribution. Mean: The arithmetic average of scores in a distribution obtained by adding the scores and then dividing by their number. Median: The middle score in a rank- ordered distribution.

But the mean doesn’t work in a skewed distributionmean The Median is a much better measure of the center

MEAN: includes all the values, but highly affected by outliers MODE: best used to find what is the most common category not unique (what if there are 2 modes?) not a good measure of central tendency when the mode is far away from the rest of the data ISSUES

Positively Skewed Negatively Skewed Skewed distributions Normal Distribution

Measures of Variation Statistical dispersion: how distributed the data points are Two key ways of measuring statistical dispersion » Range » Standard Deviation

Range The range simply gives the lowest and highest values of a data set.

ETHICS a system of moral principles; rules of conduct Set by the APA: American Psychological Association

Individually: (10 min) Read the guidelines dealing with human and animal subjects Read the scenarios and check off whether the situation is ethical, unethical, or undecided Note your rationale (reasoning/justification) as you go along. In groups: (minimum of 4) Discuss each situation and collectively decided if the situation is ethical or not Answer the reflection questions (1 paper per group) Ethics Practice

Warm Up….in your notes What are three topics or issues that we have covered in this unit that you’re still unfamiliar with or confused by. -Explain what you do (or don’t) know

Standard Deviation gives a measure of dispersion (how spread out numbers are)– how much do scores deviate/vary from the mean? they are measures of the average difference between the values. It better gauges whether scores are packed together or dispersed

Formulas for Standard Deviation

Standard Deviation

Standard Deviation in Action A couple needs to be within one standard deviation of each other in intelligence (10 points in either direction). —Neil Clark Warren, founder of eHarmony.com

Normal Distributions The distribution of data also gives us key info. We know that many human attributes… e.g height, weight, task skill, reaction time, anxiousness, personality characteristics, attitudes etc. …follow a normal distribution.

IQ follows a Normal Distribution Mean = 100 SD = 15

What percentage score below 100? Mean = 100 SD = 15

What percentage score below 100? Mean = 100 SD = 15

What percentage score above 100? Mean = 100 SD = % % + 2.1%

Normal Distribution

What percentage score between 85 and 100? Mean = 100 SD = %

Normal Distribution

What percentage score between 85 and 115? Mean = 100 SD = % % = 68.2%

What percentage score between 70 and 130? Mean = 100 SD = % % % % = 95.4%

What percentage score below 70 and above 130? Mean = 100 SD = 15

Unit Review Look over the general outline of topics and concepts for the past unit. Create a concept map to synthesize and connect the information and ideas. You should be including detailed info (strengths/weaknesses/influences /applications) for the topics you’re most unfamiliar with

Figure 6. The distribution of IQ scores in male and female populations. Adjusted parameter values yielded a male-female gap of SD in g equivalent to 2.43 IQ points in favor of men Interpret this graph

Inferential Statistics You are trying to reach conclusions that extend beyond just describing the data. These are used to test hypothesis about samples. Outline

Testing for Differences If we have results (means) from two groups, before we infer causation we must ask the question: Is there a real difference between the means of the two groups or did it just happen by chance? To answer the question, we must run a t-Test

Example of when to do a t-test Does caffeine improve our reaction time? We recruit 40 people and give (random assignment) » 20 a caffeine pill (experimental group) » 20 a sugar pill (control group) We give them a brief reaction time test and record the results.

Experimental Group results (caffeine) » Mean = ms » SD = ms Control Group results (placebo) » Mean = ms » SD = Example of when to do a t-test

CaffeineNo Caffeine Example of when to do a t-test

Why can’t I be done! Yes, they are different... But you don’t know if that difference was due to your IV (caffeine) or just dumb luck. You have to be sure that the results are statistically significant

T-Test formula

T-test excel formula =TTEST(array1,array2,tails,type) Array1 is the first data set. Array2 is the second data set. Tails specifies the number of distribution tails. If tails = 1, TTEST uses the one-tailed distribution. If tails = 2, TTEST uses the two-tailed distribution. Type is the kind of t-Test to perform. IF TYPE EQUALSTHIS TEST IS PERFORMED 1Paired 2Two-sample equal variance (homoscedastic) 3Two-sample unequal variance (heteroscedastic)

T-test yields a p-value Generally, the t test gives a P value that allows us a measure of confidence in the observed difference. It allows us to say that the difference is real and not just by chance. A p value of less than 0.05 is a common criteria for significance. We call this statistically significant

T-test results Does caffeine improve our reaction time? Caffeine condition has a lower mean RT. We run a t-test on our samples and get: » p = Can we be confident that the difference in the data is not due to chance? two groups, an ANOVA tests the difference between the means of two or more groups.

Confidence Level and Intervals Confidence Interval: In statistics, a confidence interval is a particular kind of interval estimate of a population parameter. Instead of estimating the parameter by a single value, an interval likely to include the parameter is given. e.g. 40±2 or 40±5%. Confidence Level: Also called confidence coefficient, Confidence level represent the possibility that the confidence interval is to contain the parameter. e.g. 95% confidence level. Population Size: In statistics, population is the entire entities concerning which statistical inferences are to be drawn. The population size is the total number of the entire entities. Sample Size Calculator

95% Confidence Level