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Statistics
Statistics for Business
1. Introduction to Business Statistics
2. Descriptive Statistics
3. Probability Theory
4. Sampling and Sampling Distributions
5. Statistical Inference: Estimation
6. Statistical Inference: Hypothesis Testing
7. Regression Analysis
8. Time Series Analysis and Forecasting
9. Statistical Quality Control
10. Decision Analysis
Statistical Inference: Hypothesis Testing
Fundamentals of Hypothesis Testing
Null Hypothesis
Alternative Hypothesis
One-Tailed Tests
Two-Tailed Tests
Type I Error
Type II Error
Level of Significance
Power of a Test
Test Statistics
P-Value Approach
Calculation
Interpretation
Decision Rules
Critical Value Approach
Rejection Regions
Non-Rejection Regions
Decision Rules
One-Sample Tests
Test for Population Mean
Known Population Standard Deviation
Unknown Population Standard Deviation
Large Sample Tests
Small Sample Tests
Test for Population Proportion
Large Sample Test
Test Statistic
Decision Rules
Test for Population Variance
Chi-Square Test
Two-Sample Tests
Comparing Two Population Means
Independent Samples
Equal Variances
Unequal Variances
Dependent Samples
Paired t-Test
Comparing Two Population Proportions
Independent Samples
Test Statistic
Comparing Two Population Variances
F-Test
Assumptions
Analysis of Variance
One-Way ANOVA
Assumptions
F-Test
Between-Group Variation
Within-Group Variation
Two-Way ANOVA
Main Effects
Interaction Effects
Interpretation
Post-Hoc Tests
Tukey's HSD
Bonferroni Correction
When to Use
Chi-Square Tests
Goodness-of-Fit Test
Assumptions
Test Statistic
Test for Independence
Contingency Tables
Expected Frequencies
Test Statistic
Interpretation
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5. Statistical Inference: Estimation
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7. Regression Analysis