Modern Languages Row A Row B Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M table Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M Projection Booth table Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M R/L handed broken desk Stage Lecturer’s desk Screen 1

MGMT 276: Statistical Inference in Management Spring 2015

Schedule of readings Before next exam: February 17 th Please read chapters & Appendix D & E in Lind Please read Chapters 1, 5, 6 and 13 in Plous Chapter 1: Selective Perception Chapter 5: Plasticity Chapter 6: Effects of Question Wording and Framing Chapter 13: Anchoring and Adjustment

By the end of lecture today 2/3/15 Questionnaire design and evaluation Random versus non-random sampling techniques Dot Plots Frequency Distributions - Frequency Histograms Frequency, cumulative frequency Relative frequency, cumulative relative frequency Guidelines for constructing frequency distributions

Homework due - (February 5 th ) Assignment 4 Describing Data Visually using MS Excel Due: Thursday, February 5 th

Complete this TODAY and receive extra credit! (By February 3rd 2015)

Questionnaire Homework There are four parts: Statement of Objectives Questionnaire itself (which is the operational definitions of the objectives) Screenshot of Excel Database Creation of 2 bar graphs representing results Must be complete and must be stapled

Iterative design process Peer review is an important skill in nearly all areas of business and science. Please strive to provide productive, useful and kind feedback as you complete your peer review

Iterative design process Please exchange questionnaires with someone near you help make the product better using peer review worksheet handed out in class You have 10 minutes You have 10 minutes

Review of Homework Worksheet Hand in the peer review with the questionnaire *Hand them in together*

Sample versus census How is a census different from a sample? Census measures each person in the specific population Sample measures a subset of the population and infers about the population – representative sample is good What’s better? Use of existing survey data U.S. Census Family size, fertility, occupation The General Social Survey Surveys sample of US citizens over 1,000 items Same questions asked each year You’ve completed constructing your questionnaire…what’s the best way to get responders??

Parameter – Measurement or characteristic of the population Usually unknown (only estimated) Usually represented by Greek letters (µ) Population (census) versus sample Parameter versus statistic pronounced “mu ” pronounced “mew ” Statistic – Numerical value calculated from a sample Usually represented by Roman letters (x) pronounced “x bar ”

Simple random sampling: each person from the population has an equal probability of being included Sample frame = how you define population Sample frame = how you define population =RANDBETWEEN(1,115) Let’s take a sample …a random sample Question: Average weight of U of A football player Sample frame population of the U of A football team Or, you can use excel to provide number for random sample Random number table – List of random numbers Random number table – List of random numbers 64 Pick 64 th name on the list (64 is just an example here) Pick 24 th name on the list

Systematic random sampling: A probability sampling technique that involves selecting every technique that involves selecting every kth person from a sampling frame You pick the number Other examples of systematic random sampling 1) check every 2000 th light bulb 2) survey every 10 th voter

Stratified sampling: sampling technique that involves dividing a sample into subgroups (or strata) and then selecting samples from each of these groups - sampling technique can maintain ratios for the different groups Average number of speeding tickets 17.7% of sample are Pre-business majors 4.6% of sample are Psychology majors 4.6% of sample are Psychology majors 2.8% of sample are Biology majors 2.8% of sample are Biology majors 2.4% of sample are Architecture majors 2.4% of sample are Architecture majors etc etc Average cost for text books for a semester 12% of sample is from California 7% of sample is from Texas 6% of sample is from Florida 6% from New York 4% from Illinois 4% from Ohio 4% from Pennsylvania 3% from Michigan etc

Cluster sampling: sampling technique divides a population sample into subgroups (or clusters) by region or physical space. Can either measure everyone or select samples for each cluster Textbook prices Southwest schools Southwest schools Midwest schools Midwest schools Northwest schools Northwest schools etc etc Average student income, survey by Old main area Old main area Near McClelland Around Main Gate etc Patient satisfaction for hospital 7 th floor (near maternity ward) 7 th floor (near maternity ward) 5 th floor (near physical rehab) 5 th floor (near physical rehab) 2 nd floor (near trauma center) 2 nd floor (near trauma center) etc etc

Snowball sampling: a non-random technique in which one or more members of a population are located and used to lead the researcher to other members of the population Used when we don’t have any other way of finding them - also vulnerable to biases Convenience sampling: sampling technique that involves sampling people nearby. A non-random sample and vulnerable to bias Judgment sampling: sampling technique that involves sampling people who an expert says would be useful. A non-random sample and vulnerable to bias Non-random sampling is vulnerable to bias

You’ve gathered your data…what’s the best way to display it??

Describing Data Visually Lists of numbers too hard to see patterns Organizing numbers helps Graphical representation even more clear This is a dot plot

Describing Data Visually Measuring the “frequency of occurrence” Then figure “frequency of occurrence” for the bins We’ve got to put these data into groups (“bins”)

Frequency distributions Frequency distributions an organized list of observations and their frequency of occurrence How many kids are in your family? What is the most common family size?

Another example: How many kids in your family? Number of kids in family

Frequency distributions Crucial guidelines for constructing frequency distributions: 1. Classes should be mutually exclusive: Each observation should be represented only once (no overlap between classes) 2. Set of classes should be exhaustive: Should include all possible data values (no data points should fall outside range) Wrong Correct Correct 0 - under under under 15 How many kids are in your family? What is the most common family size? Number of kids in family Wrong Correct No place for our families of 4, 5, 6 or 7

Frequency distributions Crucial guidelines for constructing frequency distributions: 3. All classes should have equal intervals (even if the frequency for that class is zero) Wrong Correct Correct 0 - under under under 15 How many kids are in your family? What is the most common family size? Number of kids in family

4. Selecting number of classes is subjective Generally will often work How about 6 classes? (“bins”) How about 8 classes? (“bins”) How about 16 classes? (“bins”)

5. Class width should be round (easy) numbers 6. Try to avoid open ended classes For example 10 and above Greater than 100 Less than 50 Clear & Easy Round numbers: 5, 10, 15, 20 etc or 3, 6, 9, 12 etc Lower boundary can be multiple of interval size Remember: This is all about helping readers understand quickly and clearly.

Let’s do one Scores on an exam If less than 10 groups, “ungrouped” is fine If more than 10 groups, “grouped” might be better How to figure how many values = 47 Step 1: List scores Step 2: List scores in order Step 3: Decide whether grouped or ungrouped Step 4: Generate number and size of intervals (or size of bins) Largest number - smallest number + 1 Sample size (n) 10 – – – – – – 1,024 Number of classes If we have 6 bins – we’d have intervals of 8 Whaddya think? Would intervals of 5 be easier to read? Let’s just try it and see which we prefer…

Scores on an exam Scores on an exam Score Frequency – Scores on an exam Score Frequency bins Interval of 5 6 bins Interval of 8 Let’s just try it and see which we prefer… Remember: This is all about helping readers understand quickly and clearly. Scores on an exam Score Frequency –

Scores on an exam Scores on an exam Score Frequency – Let’s make a frequency histogram using 10 bins and bin width of 5!!

Scores on an exam Score Frequency – Step 6: Complete the Frequency Table Scores on an exam Cumulative Frequency Relative Frequency Relative Cumulative Frequency bins Interval of 8 Just adding up the frequency data from the smallest to largest numbers Just dividing each frequency by total number to get a ratio (like a percent) Please note: 1 /28 = / 28 = /28 =.1429 Just adding up the relative frequency data from the smallest to largest numbers Please note: Also just dividing cumulative frequency by total number 1/28 = /28 = /28 =.1786

Who is your favorite candidate Candidate Frequency Mitt Romney84 Jeb Bush68 Dr. Ben Carson 60 Scott Walker44 Ted Cruz36 Mike Huckabee36 Chris Christy28 Undecided20 Rand Paul16 Rick Perry 8 Homework Preview Simple Frequency Table – Qualitative Data We asked 400 Republicans “Who is your favorite candidate?” Relative Frequency Just divide each frequency by total number Please note: 80 /400 = /400 = /.400 =.1500 Percent 21% 17% 15% 11% 9% 7% 5% 4% 2% If one million Republicans voted today how many would vote for each candidate? Number expected to vote 210, , , ,000 90,000 70,000 50,000 40,000 20,000 Just multiply each relative frequency by 100 Please note:.2100 x 100 = 21%.1700 x 100 = 17%.1500 x 100 = 15% Just multiply each relative frequency by one million Please note:.2100 x million = 210, x million = 170, x million = 150,000 Data from January 30 th 2015

Describing Data Visually Measuring the “frequency of occurrence”

Scores on an exam Scores on an exam Score Frequency – Remember Dot Plots Score on exam Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 5: Generate frequency histogram

Scores on an exam Scores on an exam Score Frequency – Score on exam Remember Dot Plots Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 5: Generate frequency histogram

Scores on an exam Scores on an exam Score Frequency – Score on exam Remember Dot Plots Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 5: Generate frequency histogram

Scores on an exam Scores on an exam Score Frequency – Score on exam Remember Dot Plots Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 5: Generate frequency histogram

Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Scores on an exam Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Scores on an exam Score Frequency – Step 5: Generate frequency histogram Score on exam

Scores on an exam Scores on an exam Score Frequency – Score on exam Generate frequency polygon Plot midpoint of histogram intervals Connect the midpoints

Scores on an exam Scores on an exam Score 95 – – Score on exam Frequency ogive is used for cumulative data Generate frequency ogive (“oh-jive”) Cumulative Frequency Connect the midpoints Plot midpoint of histogram intervals

Pareto Chart: Categories are displayed in descending order of frequency

Stacked Bar Chart: Bar Height is the sum of several subtotals

Simple Line Charts: Often used for time series data (continuous data) (the space between data points implies a continuous flow) Note: Can use a two-scale chart with caution Note: Fewer grid lines can be more effective Note: For multiple variables lines can be better than bar graph

Pie Charts: General idea of data that must sum to a total (these are problematic and overly used – use with much caution) Bar Charts can often be more effective Exploded 3-D pie charts look cool but a simple 2-D chart may be more clear Exploded 3-D pie charts look cool but a simple 2-D chart may be more clear

Data based on Gallup poll on 8/24/11 Who is your favorite candidate Candidate Frequency Rick Perry29 Mitt Romney17 Ron Paul13 Michelle Bachman10 Herman Cain 4 Newt Gingrich 4 No preference23 Simple Frequency Table – Qualitative Data We asked 100 Republicans “Who is your favorite candidate?” Relative Frequency Just divide each frequency by total number Please note: 29 /100 = /100 = /100 = /100 =.0400 Percent 29% 17% 13% 10% 4% 23% If 22 million Republicans voted today how many would vote for each candidate? Number expected to vote 6,380,000 3,740,000 2,860,000 2,200, ,000 5,060,000 Just multiply each relative frequency by 100 Please note:.2900 x 100 = 29%.1700 x 100 = 17%.1300 x 100 = 13%.0400 x 100 = 4% Just multiply each relative frequency by 22 million Please note:.2900 x 22m = 6,667k.1700 x 22m = 3,740k.1300 x 22m = 2,860k.0400 x 22m= 880k