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
Model test. Click here for details. [view results]
Final Exam
August 23 at 11:00 AM. [view results]
Makeup Test
August 24 at 11:30 AM. Click here for details.