Share Description
In this course, you will learn :
- Describe how to compute simple probability.
- Examine the Excel statistical formulas for calculating the mean, median, and mode.
- When calculating variance, distinguish statistical nomenclature.
- When graphing frequency polygons, identify the components.
- Explain the operation of t-distributions.
- Describe the procedure for calculating a chi-square.
Syllabus :
1. Excel Statistics Fundamentals
- Using Excel functions
- Understanding Excel statistics functions
- Working with Excel graphics
- Installing the Excel Analysis Toolpak
2. Types of Data
- Differentiating data types
- Independent and dependent variables
3. Probability
- Defining probability
- Calculating probability
- Understanding conditional probability
4. Central Tendency
- The mean and its properties
- Working with the median
- Working with the mode
5. Variability
- Understanding variance
- Understanding standard deviation
- Z-scores
6. Distributions
- Organizing and graphing a distribution
- Graphing frequency polygons
- Properties of distributions
- Probability distributions
7. Normal Distributions
- The standard normal distribution
- Meeting the normal distribution family
- Standard normal distribution probability
- Visualizing normal distributions
8. Sampling Distributions
- Introducing sampling distributions
- Understanding the central limit theorem
- Meeting the t-distribution
9. Estimation
- Confidence in estimation
- Calculating confidence intervals
10. Hypothesis Testing
- The logic of hypothesis testing
- Type I errors and Type II errors
11. Testing Hypotheses about a Mean
- Applying the central limit theorem
- The z-test and the t-test
12. Testing Hypotheses about a Variance
- The chi-squared distribution
13. Independent Samples Hypothesis Testing
- Understanding independent samples
- Distributions for independent samples
- The z-test for independent samples
- The t-test for independent samples
14. Matched Samples Hypothesis Testing
- Understanding matched samples
- Distributions for matched samples
- The t-test for matched samples
15. Testing Hypotheses about Two Variances
- Working with the F-test
16. The Analysis of Variance
- Testing more than two parameters
- Introducing ANOVA
- Applying ANOVA
17. After the Analysis of Variance
- Types of post-ANOVA testing
- Post-ANOVA planned comparisons
18. Repeated Measures Analysis
- What is repeated measures?
- Applying repeated measures ANOVA
19. Hypothesis Testing with Two Factors
- Statistical interactions
- Two-factor ANOVA
- Performing two-factor ANOVA
20. Regression
- Understanding the regression line
- Variation around the regression line
- Analysis of variance for regression
- Multiple regression analysis
21. Correlation
- Hypothesis testing with correlation
- Understanding correlation
- The correlation coefficient
- Correlation and regression
