### Class History: Business Statistics (Summer 2017) This page summarizes all the classes (including extra classes) of the course Business Statistics in the Summer 2017 semester.

## Summary

• Class time: Monday 12:30 PM (Room: 602). Wednesday 12:30 PM (Room: 602).
• Regular classes: 17
• Extra classes: 5
• Total classes: 22

## Class 1

May 8, Time 12:35-1:50, Room 602

An overview of the whole course.

Chapter 1.

What is statistics. Short and long definition of statistics. Data and information, using examples. Differences between data and information.

## Class 2

May 17, Time 1:00-1:55, Room 602

Types of data -- non-numerical or qualitative data, numerical or quantitative data. Types of numerical data -- discrete and continuous variable. Levels of measurement -- nominal, ordinal, interval, and ratio level data.

## Class 3

May 22, Room 602, Time 12:30 -2:00

Types of statistics -- descriptive and inferential. Population and sample. Reasons for using sample instead of population.

Chapter 2.

The summation sign -- mathematical problem. Population mean. Sample mean. Five properties of mean, with mathematical examples.

## Class 4

May 24, Room 602, Time 12:30 -1:50

Weighted mean. Other approaches of measuring central tendency -- mode (including math) and Median (including math). Advantages and disadvantages of Median.

Chapter 3.
Why study dispersion. Methods of calculating dispersion -- an overview. Range (with math).

## Class 5

May 29, Room 602, Time 12:25 -1:30

Problems of range. Mean deviation (math). Problems of mean deviation. Variance (math). Problems of variance.

## Class 6

June 5, Room 602, Time 12:30 -1:30

Standard deviation. Interpretation of standard deviation. Skewness calculation and explanation. Meaning of positive, zero, and negative skewness.

## Class 7

June 7, Room 602, Time 1:00 - 2:15

Review of the midterm syllabus. Problem solving.

## Class 8 (Extra), Class 9 (Extra)

June 13, Room B2-201

Time 2:30 - 3:30 (class 8), and 3:30 - 4:30 (class 9)

Review of the mathematical problems of Chapter 2 and 3. Problem solving.

## Midterm Exam

June 14, Room 801, Time 10:00 - 11:30.

Syllabus: Chapter 1 to 3. [view results]

## Class 10

July 5, Room 602, Time 12:40 - 1:50

Chapter 4.

Charts and graphs. How to present numerical data in pie chart -- details. Histogram and bar charts. Presenting numerical data in histogram -- practical (graph papers were given to each student).

## Class 11

July 10, Room 602, Time 1:00 - 2:00

Frequency distribution defined. Math: frequency distribution. Drawing a histogram from frequency distribution, on graph paper. Math: relative frequency distribution and cumulative frequency distribution. Important things to concern in a frequency distribution.

## Class 12

July 12, Room 603, Time 1:00 - 2:15

Math: construct a frequency polygon on graph paper based on a frequency distribution (graph papers were given to each student).

## Class 13 (Extra)

July 13, Room 602, Time 2:30 - 3:30

Math: Textbook (16ed) pg.31 problem no. 12 Frequency distribution, relative frequency distribution, frequency polygon (on graph paper).

## Class 14

July 17, Room 602, Time 12:50 - 2:00 PM

Class test 1: Format: Mathematical problems and graph. Syllabus: Frequency distribution, relative frequency distribution, and frequency polygon. Graph papers were given to each student. Click here for details. [view results]

## Class 15

July 29, Room 601, Time 2:30 - 3:50 PM

This is the substitute of the class of July 19.

Chapter 6. Correlation defined. The concept of correlation explained.

Mathematical problem: six months data of ad expenses and revenues are given. Find out the Pearson correlation between ad expenses and revenues.

## Class 16

July 31, Room 602, Time 12:30 - 2:05 PM

Difference between Pearson's correlation and Spearman’s correlation. When to use Spearman correlation. Estimating correlations from graphs. Correlation and cause.

Math: (1) Spearman’s correlation. (2) Coefficient of determination.

## Class 17

August 2, Room 602, Time 12:30 - 2:10 PM

Chapter 7. Regression analysis, dependent variable, and independent variables. Mathematical problem: x = advertisement expenses, y = revenue. Find out the value of y for a particular x.

Assignment 1 (individual).

## Class 18

August 7, Room 602, Time 12:50 - 2:10

The line of regression.

Properties of the line of regression:

Crosses Y at “a”

Crosses the mean of X and Y at a single point

Summation of squared d is minimum.

Assumptions of linear regression:

X and Y must be interval and/ or ratio level

X and Y are normally distributed

Xi is not affected by other values in the series.

## Class 19

August 9, Room 602, Time 12:40 - 2:05

Math: x, y, Sx, Sy, and r(x,y) are given. Construct regression equation, draw the regression line, and interpret your result.

Chapter 5. Probability defined. Empirical and classical probability. General and special rules of addition. Math: general rule of addition, with graph.

## Class 20 (Extra)

August 11, Room B2-103, Time 12:00 - 1:20

Review: Pearson's correlation and regression.

How to use calculator efficiently?

## Class 21 (Extra)

August 11, Room B2-103, Time 14:40 - 3:30

Review: Spearman’s correlation.

## Class 22

August 16, Room 603, Time 1:15 - 2:30