PY 281 - Introduction to Statistics

1. Demonstrate understanding of the basic principles of data collection, observational study, and experimental design.
2. Construct and interpret graphical and tabular displays of univariate data.
3. Summarize distributions of univariate data using measures of central tendency, measures of dispersion, and measures of location.
4. Compare multiple data sets with graphical displays and numerical measures.
5. Perform basic probability computations.
6. Solve problems by applying appropriate probability distributions.
7. Use the Central Limit Theorem to model sampling distributions and compute probabilities based on sampling distributions.
8. Analyze bivariate quantitative data.
9. Construct and interpret confidence intervals of proportion or mean for one population.
10. Construct and interpret confidence intervals for the difference of proportions or means for two populations.
11. Perform hypothesis tests for the means and proportions for one population.
12. Perform hypothesis tests for the difference of proportions or means for two populations.
13. Interpreting p-value, type I and type II errors, and statistical and practical significance.
14. Input, interpret and apply output from SPSS software.
15. Interpret and apply appropriate statistical techniques and concepts to real-life data and situations in the behavior and psychological sciences in order to make decisions and/or draw conclusions.
16. Analyze bivariate qualitative data presented in two-way tables and interpret relationships between categorical variables using chi-square tests.
17. Perform hypothesis tests including the goodness-of-fit test and ANOVA.
18. Create a written summary of the main ideas extracted from information gathered. 
19. Clearly and completely state and describe a problem/issue. 
20. Create and/or organize data and information into meaningful patterns in order to interpret and draw inferences from it. 
21. Complete work accurately, with attention to detail. 

II. Central Tendency and Variability

III. Introduction to Research Design

IV. Core Concepts in Inferential Statistics: Z Scores, the Normal Curve, Sample versus Population, and Probability

V.Introduction to Hypothesis Testing with Z Scores

VI.Hypothesis Tests with Means of Samples

VII. Making Sense of Statistical Significance: Decision Errors, Effect Size, and Statistical Power

VIII. Introduction to t Tests: Single Sample and Dependent Means

IX.The t Test for Independent Means

X. Data Collection and Reporting Inferential Statistics in Research

XI. Introduction to the Analysis of Variance (ANOVA)

XII. Correlation

XIII. Prediction

XIV. Chi-Square Tests (Goodness of Fit, Test for Independence)

Facilitated discussion: 10-40%

Group work: 0-40%

Assisted individual work: 0-30%