Mgmt 276 statistical inference in management spring 2014
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MGMT 276: Statistical Inference in Management Spring, 2014. Welcome. Green sheets. http://www.youtube.com/watch?v=Ahg6qcgoay4&watch_response. Use this as your study guide. By the end of lecture today 1/28/14. Single versus Double Blind Studies Nominal, Ordinal, Interval, Ratio

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MGMT 276: Statistical Inference in Management Spring, 2014

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Mgmt 276 statistical inference in management spring 2014

MGMT 276: Statistical Inference in ManagementSpring, 2014

Welcome

Green sheets

http://www.youtube.com/watch?v=Ahg6qcgoay4&watch_response


By the end of lecture today 1 28 14

Use this as your

study guide

By the end of lecture today1/28/14

Single versus Double Blind Studies

Nominal, Ordinal, Interval, Ratio

Categorical vs Numerical

(Quantitative vs Qualitative)

Time series design vs. Cross sectional design

Descriptive versus inferential analyses


Announcements

Announcements

Notetakers

Name

Major

email

phone #


Mgmt 276 statistical inference in management spring 2014

Remember bring your

writing assignment forms

notebook and clickers to each lecture

A noteon doodling

Talking or whispering to your neighbor can be a problem for us – please consider writing short notes.

Complete this in the next two weeks and receive extra credit!

(By February 4th)


Mgmt 276 statistical inference in management spring 2014

Please click in

My last name starts with a

letter somewhere between

A. A – D

B. E – L

C. M – R

D. S – Z


Mgmt 276 statistical inference in management spring 2014

Homework due - (January 30th)

On class website: please print and complete homework worksheet #1

Please double check – Allcell phones other electronic devices are turned off and stowed away


Mgmt 276 statistical inference in management spring 2014

Schedule of readings

Before next exam:

Please read chapters 1 - 4 &

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


So far

So far,

Measurement: observable actions

Theoretical constructs: concepts (like “humor” or “satisfaction”)

Operational definitions

Validity and reliability

Independent and dependent variable

Random assignment and Random sampling

Within-participant and between-participant design

Single blind (placebo) and double blind procedures


Continuous versus discrete

Duration

Continuous versus discrete

Continuous variable: Variables that can assume any value. There are

(in principle) an infinite number of values between any two numbers

Discrete variable: Variables that can only assume whole numbers.

There are no intermediate values between the whole numbers

Distance

Number of kids

Height

Number of eggs in a carton

Number of textbooks required for class


Categorical versus numerical data

Categorical versus Numerical data

Categorical data (also called qualitative data)

- a set of observations where any single observation is a

word or a number that represents a class or category

Numerical data (also called quantitative data)

- a set of observations where any single observation is a

number that represents an amount or count


Mgmt 276 statistical inference in management spring 2014

Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category

Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count

Handedness - right handed or left handed

Family size

Hair color

Ethnic group

GPA

Age

Yearly salary

Breed of dog

Gender - male or female

Temperature

Please note this is a binary variable


Mgmt 276 statistical inference in management spring 2014

Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category

Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count

On a the top half of a writing assignment form

please generate two examples of categorical

data and two examples of numerical data

Please note we’ll use the bottom half for something else


What are the four levels of measurement

What are the four “levels of measurement”?

Categorical data

  • Nominal data - classification, differences in kind, names of categories

  • Ordinal data - order, rankings, differences in degree

Numerical data

  • Interval data - measurable differences in amount, equal intervals

  • Ratio data - measurable differences in amount with a “true zero”


What are the four levels of measurement1

What are the four “levels of measurement”?

Categorical data

  • Nominal data - classification, differences in kind, names of categories

  • Ordinal data - order, rankings, differences in degree

Numerical data

  • Interval data - measurable differences in amount, equal intervals

  • Ratio data - measurable differences in amount with a “true zero”

Gender - male or female

Family size

Jersey number

Place in a foot race (1st, 2nd, 3rd, etc)

Handedness - right handed or left handed


What are the four levels of measurement2

What are the four “levels of measurement”?

Categorical data

  • Nominal data - classification, differences in kind, names of categories

  • Ordinal data - order, rankings, differences in degree

Numerical data

  • Interval data - measurable differences in amount, equal intervals

  • Ratio data - measurable differences in amount with a “true zero”

Age

Hair color

Telephone number

Ethnic group

Breed of dog

Temperature

Yearly salary


Mgmt 276 statistical inference in management spring 2014

Please note :

page 29 in text


What are the four levels of measurement3

What are the four “levels of measurement”?

Categorical data

  • Nominal data - classification, differences in kind, names of categories

  • Ordinal data - order, rankings, differences in degree

Numerical data

  • Interval data - measurable differences in amount, equal intervals

  • Ratio data - measurable differences in amount with a “true zero”

Look at your examples of qualitative and quantitative data.

Which levels of measurement are they?


Descriptive vs inferential statistics

Descriptive vs inferential statistics

Descriptive statistics - organizing and summarizing data

Inferential statistics - generalizing beyond actual observations

making “inferences” based on data collected


Descriptive or inferential

Descriptive or inferential?

Descriptive statistics - organizing and summarizing data

Inferential statistics - generalizing beyond actual observations

making “inferences” based on data collected

What is the average height of the basketball team?

Measured all of the players and reported the average height

Measured only a sample of the players and reported the average height for team

In this class, percentage of students who support the death penalty?

Measured all of the students in class and reported percentage who said “yes”

Measured only a sample of the students in class and reported percentage who said “yes”

Based on the data collected from the students in this class we can

conclude that 60% of the students at this university support the death penalty

Measured all of the students in class and reported percentage who said “yes”


Descriptive or inferential1

Descriptive or inferential?

Descriptive statistics - organizing and summarizing data

Inferential statistics - generalizing beyond actual observations

making “inferences” based on data collected

Men are in general taller than women

Measured all of the citizens of Arizona and reported heights

Shoe size is not a good predictor of intelligence

Measured all of the shoe sizes and IQ of students of 20 universities

Blondes have more fun

Asked 500 actresses to complete a happiness survey

The average age of students at the U of A is 21

Asked all students in the fraternities and sororities their age


Descriptive vs inferential statistics1

Descriptive vs inferential statistics

Descriptive statistics - organizing and summarizing data

Inferential statistics - generalizing beyond actual observations

making “inferences” based on data

collected

To determine this we have to consider the

methodologies used in collecting the data


Mgmt 276 statistical inference in management spring 2014

Time series versus cross-sectional comparisons:

Trends over time versus a snapshot comparison

Time series design: Each observation represents a measurement

at some point in time. Repeated measurements allow us to see

trends.

Cross-sectional design: Each observation represents a

measurement at some point in time. Comparing across groups

allows us to see differences.

Traffic accidents

Please note: Any one piece of data can often (not always) be used in either a time series comparison or a cross-sectional comparison. It depends how you set up your question.

Does Tucson or Albuquerque have more traffic accidents (they have similar population sizes)?

Does Tucson have more traffic accidents as the year

ends and winter approaches?


Mgmt 276 statistical inference in management spring 2014

Time series versus cross-sectional comparisons:

Trends over time versus a snapshot comparison

Time series design: Each observation represents a measurement

at some point in time. Repeated measurements allow us to see

trends.

Cross-sectional design: Each observation represents a measurement at

some point in time. Comparing across groups allows us to see differences.

Unemployment rate

Is there an increase in workers calling in sick as the summer months approach?

Do more young workers call in sick than older workers?

Grade point average (GPA)

Does GPA tend to go up or down as students move from freshman to sophomores to juniors to seniors?

Does GPA tend to go up or down when you compare Mr. Chen’s class with Mr. Frank’s Freshman English classes?


Let s try one

Let’s try one

A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The independent variable in this study was

a. the performance of the subjects on the vision exam

b. the subjects who ate the carrots

c. whether or not the subjects ate the carrots

d. whether or not the subjects had their vision tested


Let s try one1

Let’s try one

A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The dependent variable in this study was

a. the performance of the subjects on the vision exam

b. the subjects who ate the carrots

c. whether or not the subjects ate the carrots

d. whether or not the subjects had their vision tested


Let s try one2

Let’s try one

A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. This experiment was a

a. within participant experiment

b. between participant experiment

c. mixed participant experiment

d. non-participant experiment


Let s try one3

Let’s try one

When Martiza was preparing her experiment, she knew it was important that the participants not know which condition they were in, to avoid bias from the subjects.

This is called a _____ study.

She also was careful that the experimenters who were interacting with the participants did not know which condition those participants were in.

This is called a ____ study.

a. between participant; within participant

b. within participant; between participant

c. double blind design; single blind

d. single blind; double blind design


Let s try one4

Let’s try one

A measurement that has high validity is one that

a. measures what it intends to measure

b. will give you similar results with each replication

c. will compare the performance of the same subjects

in each experimental condition

d. will compare the performance of different subjects

in each experimental condition


Let s try one5

Let’s try one

A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers ask 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. The independent variable in this study was

a. the performance of the activists

b. the number of bumper stickers found on their car

c. political status of participant (liberal versus conservative) as determined by their performance on the liberal/conservative test

d. whether or not the subjects had bumper stickers on their car


Let s try one6

Let’s try one

A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers asked 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. The dependent variable in this study was

a. the performance of the activists

b. the number of bumper stickers found on their car

c. political status of participant (liberal versus conservative) as determined by their performance on the liberal/conservative test

d. whether or not the subjects had bumper stickers on their car


Let s try one7

Let’s try one

A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. This study was a

a. within participant experiment

b. between participant experiment

c. mixed participant experiment

d. non-participant experiment


Let s try one8

Let’s try one

A study explored whether conservatives or liberals had more bumper stickers on their cars. They had 100 activists complete liberal/conservative test. Then, they split the 100 activists into 2 groups (conservatives and liberals). They then measured how many bumper stickers each activist had on their car. This study used a

a. true experimental design

b. quasi-experiment design

c. correlational design

d. mixed design


Writing assignment pop quiz

Writing Assignment – Pop Quiz

Section 1 only


Mgmt 276 statistical inference in management spring 2014

Thank you!

See you next time!!


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