1 STAT 500 – Statistics for Managers STAT 500 Statistics for Managers

2 STAT 500 – Statistics for Managers Course Objectives Define and explain the relationships of statistics to other business areas Use the techniques or procedures necessary for manipulating or applying the concepts Apply what has been learned to the solution of practical problems in the business and economics areas through the development, evaluation, and selection of alternative statistical techniques. 2 STAT 500 – Statistics for Managers Course Objectives Identify the nature of statistics, it’s objective, and how it plays an important role in many fields in real life. Gain knowledge of data collection, summary, and analysis  Be able to describe the data set by using graphical and numerical descriptive methods. Know how sample statistics and their probability distributions are used to make inferences about sampled populations.

33 STAT 500 – Statistics for Managers Course Objectives (Continued) Understand the concepts of the estimation and test procedures for population parameters as well as to use. some useful tools for solving some practical problems. Get a good idea of basic forecasting techniques.  Make real world forecasts.  Apply what has been learned to the solution of practical problems in the business and economics areas through the development, evaluation, and selection of alternative statistical techniques.

4 STAT 500 – Statistics for Managers Textbook  Levine David and Berenson Mark, (1997) Statistics for Managers  Bowerman B. and O'Connell (1993), Forecasting and Time Series Bowerman

5 STAT 500 – Statistics for Managers Course Topics Introduction Descriptive Statistics Probability Discrete Random variables Continuous Random variables Sampling

6 STAT 500 – Statistics for Managers Course Topics (Continued) Estimation: Confidence Intervals Hypothesis Testing Simple Regression & Correlation Multiple Regression

7 STAT 500 – Statistics for Managers Course Topics (Continued) Forecasting by using regression analysis Time series Forecasting by using time series analysis Practical cases.

8 STAT 500 – Statistics for Managers Grading Scheme Assignments (20%) There will be in all four assignments. I will consider the best three out of four assignments. Mid Term examination (30%) Term Paper (10%)

9 STAT 500 – Statistics for Managers The term paper will be a critique (good and bad aspects) on an article containing statistical analysis. You may be able to locate such an article in a newspaper or a magazine or a journal. Final Examination (40%) The final examination would cover the entire coursework but emphasis would be on the material covered during the period after the mid-term examination.

10 STAT 500 – Statistics for Managers Why a Manager for example needs to know about Statistics? To know how to properly present and describe information To know how to draw conclusions about large populations based only on information obtained from samples To know how to improve processes To know how to obtain reliable forecasts of variables of interest.

11 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

12 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

13 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

14 STAT 500 – Statistics for Managers Descriptive Statistics Deals with –Collecting data, e.g., survey –Presenting data, e.g., graphs and tables –Characterizing data, e.g., mean, standard deviation, etc. Objective –Describe data _ _

15 STAT 500 – Statistics for Managers Inferential Statistics Deals with –Estimation of population parameters –Hypothesis Testing Objective –Make decisions about population characteristics based on sample observations

16 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

17 STAT 500 – Statistics for Managers Some Key Terms Population (universe) –All items of interest Sample –Portion of population Parameter –Summary measure about population Statistic –Summary measure about sample

18 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

19 STAT 500 – Statistics for Managers Primary Data Collection Secondary Data Compilation Observation Experimentation Survey Print or Electronic Data Sources

20 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

21 STAT 500 – Statistics for Managers

22 STAT 500 – Statistics for Managers Examples Numerical –Discrete How many cars do you have? ___ (Number) –Continuous What is the distance between your home and office? ___ (miles) Categorical Do you like statistics course? __ Yes __ No

23 STAT 500 – Statistics for Managers Interval scale –No true 0 –e.g., Degrees Celsius Ratio scale –Equal intervals –True 0 –Meaningful ratios –e.g., Height in inches Data Measurement n Nominal scale l Categories s e.g., Male-female l Count n Ordinal scale l Categories l Ordering implied s e.g., High-low l Count

24 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation

25 STAT 500 – Statistics for Managers Organizing Numerical Data Data Detail Ordered Array Stem and Leaf Display Data Shape Histogram Frequency Polygon Ogive

26 STAT 500 – Statistics for Managers Ordered Array Data placed in rank order –Smallest to largest Raw Data –64, 66, 64, 61, 67, 67, 70, 72, 78 Data in ordered array –61, 64, 64, 66, 67, 67, 70, 72, 78

27 STAT 500 – Statistics for Managers Stem-and-Leaf Display Represent each observation in terms of stem value & leaf value –Stem value defines class –Leaf value defines frequency (count) , 64, 64, 66, 67, 67, 70, 72, 78

28 STAT 500 – Statistics for Managers Frequency Distribution Tables - Steps Determine range Select number of classes –Usually between 5 & 15 inclusive Compute class intervals (width) Determine class boundaries (limits) Compute class midpoints Count observations & assign to classes

Raw Data: 61, 64, 66, 67, 70, 72, 78, 88, 61, 102 Boundaries (Upper + Lower Boundaries) / 2 Width Frequency Distribution Tables ClassMid-PointFrequency 60 but < but < but < but < but <

30 STAT 500 – Statistics for Managers Raw Data: 61, 64, 66, 67, 70, 72, 78, 88, 61, 102 Relative Frequency Distribution Tables ClassProportion% 60 but < but < but < but < but <

31 STAT 500 – Statistics for Managers Raw Data: 61, 64, 66, 67, 70, 72, 78, 88, 61, 102 Cumulative Frequency Distribution Tables Class%Cum % 60 but < but < but < but < but < Lower Class Boundary % less than upper class boundary

32 STAT 500 – Statistics for Managers Histogram Count Lower Class Boundary Bars Touch

33 STAT 500 – Statistics for Managers What do histogram and frequency tables tell? Location (Center, Typical) –Numerical Data: Most frequent Values Spread (Variation) –In what range of classes are the majority of the data values Outliers –Data values that are very different from the bulk of the data

34 STAT 500 – Statistics for Managers Polygon Count Lower Class Boundary

35 STAT 500 – Statistics for Managers Polygon Count Mid Point Special End Point Specia l End Point

36 STAT 500 – Statistics for Managers Polygons Preferable to histograms when comparing two or more sets of data Line graph of frequencies, proportions, or percentages Plot midpoints of class intervals versus frequencies, proportions or percentages

37 STAT 500 – Statistics for Managers Ogive Upper Boundary Cumulative Frequency

38 STAT 500 – Statistics for Managers Organizing Categorical Data Bar Charts Pie Charts Pareto Diagram

39 STAT 500 – Statistics for Managers An Investor’s Portfolio Amount in $ thousands

40 STAT 500 – Statistics for Managers

41 STAT 500 – Statistics for Managers Pie Chart – Investment Portfolio

42 STAT 500 – Statistics for Managers Axis for line graph shows cumulati ve % invested. Axis for bar chart shows % invested in each category.

43 STAT 500 – Statistics for Managers Objectives for this session Statistics and its Relevance Distinguish descriptive & inferential statistics Define some key terms Summarize the sources of data Describe the types of data & scales Explore different methods of data representation