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

𝐶𝑉= 𝑠 𝑥 ∗100

Last week revision

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

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

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.

Activity 1: Joint Frequency Table

Joint Probability 𝑃(𝐴⋂𝐵)

Marginal Probability 𝑃(𝐴)

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

Activity 2: Probability Table

Activity 3: Independent Events

Activity 4: Rules of Probability

Activity 5: Contingency Analysis and Chi Square Test

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

SEE YOU ALL NEXT WEEK!