This page summarizes all the classes (including extra classes) of the course Business Statistics in the Summer 2017 semester.
Class time: Monday 12:30 PM (Room: 602). Wednesday 12:30 PM (Room: 602).
Regular classes: 17
Extra classes: 5
Total classes: 22
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.
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.
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.
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).
May 29, Room 602, Time 12:25 -1:30
Problems of range. Mean deviation (math). Problems of mean deviation. Variance (math). Problems of variance.
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.
June 7, Room 602, Time 1:00 - 2:15
Review of the midterm syllabus. Problem solving.
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.
June 14, Room 801, Time 10:00 - 11:30.
Syllabus: Chapter 1 to 3. [view results]
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).
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.
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).
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).
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]
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.
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.
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).
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.
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.
August 11, Room B2-103, Time 12:00 - 1:20
Review: Pearson's correlation and regression.
How to use calculator efficiently?
August 11, Room B2-103, Time 14:40 - 3:30
Review: Spearman’s correlation.
August 16, Room 603, Time 1:15 - 2:30
Model test. Click here for details. [view results]
August 23 at 11:00 AM. [view results]
August 24 at 11:30 AM. Click here for details.