Business Statistics

1. Understand and apply basic statistical concepts and principles.
2. Calculate and interpret measures of central tendency and dispersion.
3. Perform correlation and regression analysis to determine relationships between variables.
4. Conduct hypothesis tests to make informed decisions.
5. Analyze time series data and create forecasts.
6. Apply ANOVA to compare multiple means.
7. Use statistical software to analyze data and generate reports.

13 weeks, about 46 hours in total. Yours will differ.

1. Week 1Module 1: Role and Concepts of Statistics

   • Unit 1: Role of Statistics (Application of Statistics) · 3 hours

     Understand the various definitions of statistics.. Describe the uses of statistics in different fields.. Define and differentiate basic statistical concepts such as entity, variable, and population.. Complete Exercise 1.1 to test understanding of the roles of statistics..

2. Week 2Module 1: Role and Concepts of Statistics

   • Unit 2: Measurement of Variables · 3 hours

     Define variable and distinguish between quantitative and qualitative variables.. Understand the different scales of measurement: nominal, ordinal, interval, and ratio.. Apply the appropriate measurement scale to different types of data.. Complete the tutor-marked assignment to reinforce understanding of variable measurement..

3. Week 3Module 1: Role and Concepts of Statistics

   • Unit 3: Measurement of Dispersion, Skewness and Kurtosis · 4 hours

     Calculate measures of dispersion such as range, quartile deviation, mean deviation, variance, and standard deviation.. Compute the coefficient of variation to compare variability of different data sets.. Determine the skewness and kurtosis of a distribution.. Work through the tutor-marked assignment to apply these measures to a given data set..

4. Week 4Module 1: Role and Concepts of Statistics

   • Unit 4: Decision Analysis and Administration · 4 hours

     Understand the administrative and decision-making process.. Apply analytical and creative thinking to problem-solving.. Learn about decision-making under certainty and uncertainty.. Construct a payoff table and analyze decision problems using expected monetary value..

5. Week 5Module 2: INDEX NUMBER AND SAMPLING THEORIES

   • Unit 1: Index Number · 3 hours

     Define index numbers and describe their uses.. Understand the different types of index numbers.. Identify the problems encountered in the construction of index numbers.. Calculate index numbers using simple and weighted aggregate methods.. Complete the tutor-marked assignment to practice index number calculations..

6. Week 6Module 2: INDEX NUMBER AND SAMPLING THEORIES

   • Unit 2: Statistical Data · 3 hours

     Distinguish between primary and secondary data.. Understand the advantages and disadvantages of each type of data.. Identify various sources of statistical data.. Differentiate between cross-sectional, time-series, and panel data..

7. Week 7Module 2: INDEX NUMBER AND SAMPLING THEORIES

   • Unit 3: Sample and Sampling Theory · 4 hours

     Define population, sample, sampling unit, and sampling frame.. Distinguish between probability and non-probability sampling methods.. Understand the different types of probability and non-probability sampling designs.. Discuss the factors affecting the response rate of mail questionnaires..

8. Week 8Module 2: INDEX NUMBER AND SAMPLING THEORIES

   • Unit 4: Estimation Theory · 4 hours

     Understand the theory behind estimation.. Apply estimation theory to solve business and economic problems.. Learn about methods of point estimation, including maximum likelihood.. Complete the tutor-marked assignment to practice estimation techniques..

9. Week 9Module 3: CORRELATION AND REGRESSION ANALYSIS

   • Unit 1: Correlation Theory · 3 hours

     Define correlation and understand different types of correlation.. Distinguish between positive and negative correlation.. Apply correlation theory to solve business and economic problems.. Complete the tutor-marked assignment to reinforce understanding of correlation types..

10. Week 10Module 3: CORRELATION AND REGRESSION ANALYSIS

    • Unit 2: Pearson's Correlation Co-efficient · 3 hours

      Describe the computation of linear correlation coefficients.. Apply the concept of correlations in business decisions.. Calculate Pearson's correlation coefficient for a given data set.. Interpret the results and understand the strength and direction of the relationship..

11. Week 11Module 3: CORRELATION AND REGRESSION ANALYSIS

    • Unit 3: Spearman's Regression Analysis · 4 hours

      Explain the computation of rank correlation coefficients.. Apply the concept of correlations in business decisions.. Calculate Spearman's rank correlation coefficient for a given data set.. Interpret the results and understand the strength and direction of the relationship..

12. Week 12Module 3: CORRELATION AND REGRESSION ANALYSIS

    • Unit 4: Ordinary Lease Square Estimation (Regression) · 4 hours

      Understand the theory behind regression analysis.. Apply regression analysis to solve business and economic problems.. Learn about simple and multiple regression.. Calculate regression lines using the least squares method..

13. Week 13Module 3: CORRELATION AND REGRESSION ANALYSIS

    • Unit 5: Multiple Regression Analysis · 4 hours

      Understand the theory behind multiple regression analysis.. Apply multiple regression analysis to solve business and economic problems.. Learn about non-linear models and linearization.. Complete the tutor-marked assignment to reinforce understanding of multiple regression..