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Bus 345 > Week 12 > Flashcards

Week 12 Flashcards

1
Q

What’s the before and after with control group design

A

True experimental design that involves random assignments of subjects or test units to experimental and control groups and pre and post measurements of both groups

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2
Q

Why is the difference between the pre and post measurements of the control group important

A

Provide a good estimate of the effect of all extraneous influences experienced by each group

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3
Q

What is after only with control group designs

A

The true experimental design that involves random assignment of subjects or test units to experimental and control groups but no pre measurement of the dependent variable

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4
Q

What is quasi experiments

A

Where the researcher lacks complete control over the scheduling of treatments or must assign respondents to treatments in a non random manner

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5
Q

What is interrupted time series design

A

Repeated measurements of an effect “interrupts” previous data patterns

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6
Q

Why does time series experimental designs have greater interpretability

A

The may measurements allow more understanding of the effects of extraneous variables

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7
Q

What are the two fundamental weakness of the time series design

A
  1. Inability to control history
  2. Possibility of interactive effects of testing and evaluation apprehension resulting from repeated measurements taken on test units
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8
Q

What is multiple time series design

A

Interrupted time series design with control

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9
Q

What are test markets

A

Real world testing of a new product or some element of the marketing mix use experimental or quasi experimental design

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10
Q

What are test market studies designed to provide information on which issues?

A
  1. Estimates of market share and volume
  2. Effects that the new product will have on sales of similar products already marked by the company called cannibalization rate
  3. Characteristics of consumers who buy the product
  4. Behaviour of competitors during the test
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11
Q

What are the four types of test markets

A
  1. Tradtional
  2. Scanner or electronic
  3. Controlled
  4. Stimulated
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12
Q

What traditional or standard markets

A

Involves testing the product or other elements of the marketing mix through regular channels of distribution

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13
Q

What are scanner or electronic test markets

A

Markets where research firms have panels of consumers who carry cards for use in buying products

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14
Q

What are controlled test markets

A

Managed by research suppliers who ensure that the product is distributed through the agreed upon types and numbers of outlets

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15
Q

Why are test markets be the last step of a research process

A

Test markets are expensive

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16
Q

Why are test markets important

A
  1. Provides a vehicle where the firm can obtain a good estimate of a products sales potential under realistic market conditions
  2. Test should identify weaknesses of the product and the proposed marketing strategy for the product and give management an opportunity to correct those weaknesses
17
Q

What are hypothesis test of proportions

A

Test to determine whether the difference between proportions is greater than would be expected because of sampling error

18
Q

How does hypothesis test of proportions work

A
  1. Specify the null and alternative hypothesis
  2. Specify the level of sampling error
  3. Calculate the estimated standard error, using the P value specified in the null hypothesis
  4. Calculate the test statistics
19
Q

Calculate the test statistics

A
  1. Specify the null and alternative hypothesis
  2. Specify the level of sampling error allowed
  3. Calculate the estimated sd using the value of p specified in a null hypothesis
  4. Test statistic
20
Q

When do we reject null hypothesis

A

Z-value is larger than the critical z-value

21
Q

What are the specifications required and the procedure for testing hypothesis

A
  1. Null hypothesis
  2. Alternative hypothesis
22
Q

How do you test two proportions in independent samples

A
  1. Specify the null and alternative hypothesis
  2. Set the level of sampling error alpha
  3. Calculate the estimated standard error of the differences between the two proportions
  4. Calculate the test statistic
  5. State the result
23
Q

What are analysis of variance

A

Testing the differences among the means of two or more independent samples

24
Q

What are one way anova

A

Used to analyze experimental results

25
Q

How do you anova

A
  1. Specify the null and alternative hypothesis
  2. Sum the squared differences between sample mean and the overall sample mean weighted by sample size
  3. Calculate the variation among groups measured by the mean sum of squares among groups
  4. Sum the squared differences between each observation
  5. Calculate the variation within the sample groups as measured by the mean sum of squares within groups
  6. Calculate the F statistic
  7. State the results
26
Q

What is the f-test

A

Tests of the probability that a particular calculated value could have been due to chance

27
Q

What is the p-value

A
  1. Exact probability of getting a computed test statistic that is due to chance
  2. Smaller the p-value the smaller the probability that the observed results occurred by chance
28
Q

What are bivariate techniques

A

Statistical methods of analyzing the relationship between two variables

29
Q

What are independent variables

A

Variables believed to affect the value of the dependent variable

30
Q

What are dependent variable

A

Variables expected to be explained or caused by the independent variable

31
Q

What are bivariate regression analysis

A

A statistical procedure appropriate for analyzing the relationship between two variables when one is considered the dependent variable and the other independent variable

32
Q

What is a scatter diagram

A

Graphic plots of the data with dependent variables on the Y axis and independent variables on the x and shows the nature of the relationship between two variables, linear or non linear

33
Q

What are the least squares estimation procedures

A

The least squares procedures are fairly simple math techniques that can be used to fit data for x and y to a line that be represents the relationship between two variables

34
Q

What is the regression line

A

Predicted values for Y based on a and b

35
Q

What is the strength of association

A

Estimated regression function that describes the nature of the relationship between x and y

36
Q

What is coefficient of determination

A

Percentage of the total variation in the dependent variable explained by the independent variable

37
Q

What is statistical significance of regression results

A

This is the total variation in y that is two components sum of squares of explained variation and un explained variation

38
Q

What is sum of squares due to regression

A

Variation explained by the regression

39
Q

What are error sum of squares

A

Variation not explained by regression

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