1. 26134 Business Statistics Autumn 2017
Tutorial 3: Probability Tables and Contingency Analysis B MathFin (Hons) M Stat (UNSW) PhD (UTS) mahritaharahap.wordpress.com/ teaching-areas
business.uts.edu.au

2. 𝐶𝑉= 𝑠 𝑥 ∗100

3. Last week revision

4. To calculate the sample and population measures we have to collect data.
Qualitative data-characteristic/attribute such as eye color--count
Quantitative data-measure

5. Presenting Data Graphically
Categorical Data
Numerical Data
Bar Charts to depict frequencies
Pie Charts to depict proportions
Histogram one numerical variable
Scatterplots relationship between two numerical variables

6. In statistics we usually want to statistically analyse a population but collecting data for the whole population is usually impractical, expensive and unavailable. That is why we collect samples from the population (sampling) and make conclusions about the population parameters using the statistics of the sample (inference) with some level of accuracy (confidence level).
A population is a collection of all possible individuals, objects, or measurements of interest. A sample is a subset of the population of interest.

7. Activity 1: Joint Frequency Table

8. Joint Probability
𝑃(𝐴⋂𝐵)

9. Marginal Probability
𝑃(𝐴)

10. Conditional Probability
𝑃 𝐴 𝐵 = 𝑃(𝐴⋂ 𝐵) 𝑃(𝐵)

11. Activity 2: Probability Table

12. Activity 3: Independent Events

13. Activity 4: Rules of Probability

14. Activity 5: Contingency Analysis and Chi Square Test

15. Contingency Analysis – Test for Independence (Chi-Square test)

16. SEE YOU ALL NEXT WEEK!