Statistics for Decision Making Descriptive Statistics QM Fall 2003 Instructor: John Seydel, Ph.D.

Student Objectives Resolve questions, trouble, etc. regarding homework exercises Strengthen ability to do basic descriptive statistics Calculations Visual summaries Recognize data types from primary source data instruments Know where to locate software for checkout Office XP (in particular, Excel 2002) WinXP Calculate basic interval estimate for the population mean Perform basic informal bivariate analyses

First, Some Administrative Stuff Questions about course? Materials (e.g., syllabus, homework,... ) Policies (e.g., exams, grading,... ) Expectations Other... ? Collect homework, etc. Prerequisite sheets Charts for KIVZ data Exercise 3-11 MIA: Campos, Gilbert, Harvey, Rose, Spragins First exam is in 2 weeks (descriptive statistics)

Software Needed for Class Office XP Excel PowerPoint Word If OfficeXP not feasible, get PowerPoint Viewer Download from Microsoft site Link on Handouts page of course website (untested) Windows 98 or newer (ME, 2000, XP) Where to get it: Library (check out from circulation desk) Download (only if you have broadband) Download If problems, let me know

A ReviewReview Quantitative data Mean  Just a simple average  Add the values and divide by number of observations Standard deviation  Average difference among the values  Process: Subtract the average from each value Square each result “Average” the squared results Take the square root of that result Use a histogram to chart frequencies, relative frequencies Qualitative data Frequencies and relative frequencies Use bar chart for charting

Let’s Look at the Homework Chapter 1 questions At this point, all you can do is quote the text However, these are good final exam questions Chapter 3: Let’s look at #15 Any others? How about other aspects of the assignment?

Type of analysis depends upon data: Quantitative; you’ll also see these terms  Ratio  Interval  Ordinal Qualitative; you’ll also see these terms  Ordinal  Nominal General classifications of data Information content Time frame Source Consider a survey... (see handout) Very Important: Data Type

A Quick Notation Quiz Mean Sample Population Standard deviation Sample Population Variance Range Number of Observations Elements in the population

Less important but need to be familiar with: Location  Median  Mode  Quantiles (percentiles, quartiles) Variation  Range  Min and Max  CV Both (?)  Z-score  Empirical Rule Other: skew Let’s take a look at these now... Miscellaneous Statistics

Now, a Quick Peak at InferenceInference Two types Estimation Hypothesis testing We’ll look closely at these later, but here’s something to get things started Estimating the population mean Recall the Empirical Rule Also, note that  The sample mean is an unbiased estimator of the population mean  The standard deviation is a reasonable estimator of the population standard deviation That said, we can estimate m using x-bar... This is called a confidence interval estimate

Bivariate Analyses: An Introduction for Quantitative Data Note: what we’ve been doing has dealt with a single variable at a time Summarizing its values Describing its variation Often, we want to explain that variation; we seek to know why not all the observations have the same value That is, we seek to understand relationships between two (or more) variables Hence, bivariate (or multivariate) analysis is called for

An Example: Great Northern Data Look at Income (use Excel) Average Standard deviation Why would it not be the same for all adjustors? Let’s examine how it relates to one of the other variables; which? Procedures: Scatterplot Estimate the relationship

Resolve questions, trouble, etc. regarding homework exercises Strengthen ability to do basic descriptive statistics Calculations Visual summaries Recognize data types from primary source data instruments Know where to locate software for checkout Office XP (in particular, Excel 2002) WinXP Calculate basic interval estimate for the population mean Perform basic informal bivariate analyses Summary

Appendix

Sampling Population Sample Parameter Statistic

Schematic View

Work Expectations Written work: type Computational work: Pencil, graph paper, straightedge Computer printout  Fit to page (when appropriate)  Annotate with pencil as necessary General guideline: be reasonable; e.g., if it doesn’t lend itself to typing, do it manually or with computer output

What is statistics all about? It’s about dealing with variation Summarizing information (description) Making decisions based upon that summarization Type of analysis depends on data type Numeric Categorical Description Formal  Numeric data: average and standard deviaiton  Categorical data: percentages Informal: frequency tables and charts data A Quick Overview