Applied Statistics

1. Analyze sampling distributions
2. Apply probability distributions
3. Perform analysis of variance and covariance
4. Conduct multiple regression analysis
5. Analyze time series data
6. Compute and interpret index numbers

13 weeks, about 65 hours in total. Yours will differ.

1. Week 1MODULE ONE: Statistical Inference

   • Unit 1: Sampling distribution defined · 5 hours

     Define population, sample, and sampling theory.. Discuss assumptions of normal distribution.. Evaluate parameter estimation.. Estimate sample mean and population mean..

2. Week 2MODULE ONE: Statistical Inference

   • Unit 2: Sampling distribution of proportion · 5 hours

     Calculate sampling distribution of proportion.. Calculate standard error.. Understand parameter estimation.. Compute confidence intervals..

3. Week 3MODULE ONE: Statistical Inference

   • Unit 3: Sampling distribution of difference and sum of two means · 5 hours

     Calculate sampling distribution of sum of two means.. Calculate sampling distribution of difference of two means.. Apply formulas to solve problems..

4. Week 4MODULE ONE: Statistical Inference

   • Unit 4: Probability distribution · 5 hours

     Describe the concept of probability.. Explain different probability distributions.. Calculate binomial, Poisson, and normal distributions.. Solve related problems..

5. Week 5MODULE TWO: Analysis of variance and analysis of covariance

   • Unit 1: One-way factor analysis of variance · 5 hours

     Understand the logic of ANOVA.. Calculate total sum of squares.. Calculate sum of squares between groups and within groups.. Compute F-statistic..

6. Week 6MODULE TWO: Analysis of variance and analysis of covariance

   • Unit 2: Two-way factor analysis of variance · 5 hours

     Explain the meaning of two-way ANOVA.. Test for two null hypotheses of two-way ANOVA.. Evaluate two-way ANOVA.. Understand interaction effects..

7. Week 7MODULE TWO: Analysis of variance and analysis of covariance

   • Unit 3: Analysis of covariance · 5 hours

     Define analysis of covariance.. Define covariate and adjusted Y.. Develop table of analysis of covariance.. Calculate terms for ANCOVA table..

8. Week 8MODULE 3: Multiple Regression Analysis

   • Unit 1: Estimation of multiple regressions · 5 hours

     Regress independent variables on the dependent variable.. Understand parameter estimates.. Calculate values of bo, b1, b2, ... bn.. Test for significance..

9. Week 9MODULE 3: Multiple Regression Analysis

   • Unit 2: Partial correlation coefficient · 5 hours

     Explain the meaning of correlation coefficient.. Discuss assumptions of correlation.. Explain goals of correlations.. Analyze correlation coefficient..

10. Week 10MODULE 3: Multiple Regression Analysis

    • Unit 3: Multiple correlation coefficient and coefficient of determination · 5 hours

      Estimate multiple correlation coefficient (R).. Estimate coefficient of determination.. Interpret results.. Understand the relationship between R and R^2..

11. Week 11MODULE 3: Multiple Regression Analysis

    • Unit 4: Overall test of significance · 5 hours

      Calculate F-statistics.. Check corresponding tabulated value of F-statistics.. Compare F-statistics and F-tab.. Interpret results..

12. Week 12MODULE 4: Time series analysis

    • Unit 1: Time series and its components · 5 hours

      Define time series.. Explain components of time series.. Understand methods of estimating time series.. Estimate and graphically represent the trend..

13. Week 13MODULE 4: Time series analysis

    • Unit 2: Quantitative estimation of time series · 5 hours

      Estimate time series data.. Understand methods of estimating time series.. Estimate and graphically represent the trends.. Apply least square and moving average methods..