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Data Analysis Techniques for Informed Business Decision-Making

Explore data analysis techniques summarized in "Doing Statistics for Business" textbook. Learn to analyze "Great Divide" dataset visually and numerically, identify relationships, and formulate hypotheses.

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Data Analysis Techniques for Informed Business Decision-Making

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  1. DoingStatistics for BusinessData, Inference, and Decision MakingMarilyn K. PelosiTheresa M. Sandifer Chapter 17 Make Your Case

  2. DoingStatistics for Business Chapter 17 Objectives • Summary of the Techniques Covered in your Textbook • How to Analyze the “Great Divide” Data Set

  3. DoingStatistics for Business SUMMARY OF TECHNIQUES Part Chapters Topic Part I Chapters 1 and 2 Getting Started Main idea: Sample as a snapshot of the population Part II Chapters 3, 4 and 5 Exploratory Data Analysis Main idea: Summarize the data in picture and numerical form Look for the center, the spread and trends Part III Chapters 6 and 7 The Keys That Unlock the Door to Inferential Statistics Main idea: Distributions andparameters Link between probability and inferential statistics

  4. DoingStatistics for Business SUMMARY OF TECHNIQUES (con’t) Part Chapters Topic Part IV: Chapters 8,9,and 10 Inferential Statistics Main idea: Use the sample to draw conclusions aboutthe population Part V: Chapters 11,12 and 13 Relationships, Models and Modeling Main idea: Use sample data to build a model to explain the relationship between 2 or more variables. Part VI Chapters 14,15,16 and 17 Additional Topics

  5. DoingStatistics for Business 4 MAJOR THEMES 1. Sampling Error 2. Variability 3. Relationships Between Variables 4.Decision Making in any Form should be Based on a Proper Analysis of Data..

  6. DoingStatistics for Business HOW TO ANALYZE THE “GREAT DIVIDE” DATA SET • Step 1: Explore the data visually using the graphical techniques of descriptive statistics. These include bar charts, pie charts and histograms. • Step 2: Summarize the data numerically. This includes finding the mean, median, quartiles, range and standard deviation (at a minimum). • Step 3: Look for relationships in the data visually and numerically. Visually you would examine scatter plots.

  7. DoingStatistics for Business HOW TO ANALYZE THE “GREAT DIVIDE” DATA SET • Step 3 (con’t): Numerically, you should use cross tabulation tables to examine averages and standard deviations for subsets of the data. • Step 4: On the basis of the results of steps 1-3, formulate some hypotheses that might help you answer your questions and solve the problem. • Step 5: Test the hypotheses, being sure to check that the assumptions of the test are not violated.

  8. DoingStatistics for Business HOW TO ANALYZE THE “GREAT DIVIDE” DATA SET • Step 6: If there appears to be a pattern in the data over time, use a time series technique. • Step 7: If appropriate, estimate the parameters of a multiple regression model for the variable you are trying to predict. • Step 8: Draw some conclusions from your analysis and make some recommendations.

  9. Doing Statistics for Business Chapter 17 Summary In this chapter you have: • Taken a global look at the techniques you learned in this textbook, Doing Statistics for Business. • Grouped the chapters into 5 main parts and found 4 themes that tie all of your work in this textbook together.

  10. Doing Statistics for Business Chapter 17 Summary (con’t) • Learned the basic tools to allow you to use data and make informed business decisions. • Learned not only to to analyze data, but that your analysis must always be done ethically and fairly.

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