Statistics for Behavioral Science Majors
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- 1: Naming, Collecting Data and Research Design
- In today’s society, we are bombarded with data on all forms of media. The question is who, how and where does the data originate. That’s why I am excited about this chapter because we will explore types of data and its’ influences of collecting the data.
- 2: Descriptive Statistics
- Both graphical and numerical methods of summarizing data make up the branch of statistics known as descriptive statistics. This section introduces numerical measurements to describe sample data.
- 3: Probability
- The basic principles of probability, including complements, union/intersection, independence, conditional probability, and counting rules.
- 4: Discrete Probability Distributions
- Probability distributions of discrete random variables, which can only take on particular values in a range.
- 5: Continuous Probability Distributions
- Probability distributions of continuous random variables, which can take on an infinite number of random values in an interval.
- 6: Confidence Intervals for One Population
- Developing confidence intervals based on a sample for a single population.
- 7: Hypothesis Tests for One Population
- Using hypothesis testing to evaluate claims about single-population parameters.
- 8: Hypothesis Tests and Confidence Intervals for Two Populations
- Hypothesis testing and developing confidence intervals for two groups. Determining if the two groups are dependent (related) or independent (not related) from one another.
- 9: Correlation and Regression
- This chapter covers how to determine whether a linear relationship exists between sets of quantitative data, and, if it does, how to make predictions for a population based on the data.
- 11: Analysis of Variance
- The F-test (for ANOVA) is a statistical test for testing the equality of k population means. Includes discussion of one-way and two-way ANOVAs, and identifying means that differ significantly from each other using the Bonferroni test.
- 12: Nonparametric Tests
- This chapter provides alternative methods to some of the previously covered, parametric tests (z-, t-, and F-tests) when the assumptions necessary for these parametric tests are not met. Includes the sign test, Wilcoxon signed-rank test, and the Mann-Whitney U test.