## Suppose you want to model a set of interaction relationships between Catholicism

Suppose you want to model a set of interaction relationships between Catholicism, religious attendance, and abortion beliefs. You think that the positive effect of religious attendance on anti-abortion attitudes is significantly stronger for Catholics than non-Catholics. To construct the interaction model, you will build on the base effects of the model
y = a + b1(Catholic) + b2(high attendance), where “Catholic” is a Catholic/non-Catholic dummy (Catholics are coded 1, non-Catholics coded 0) and “high attendance” is a high attendance /low attendance dummy (frequent attenders are coded 1, infrequent attenders are coded 0). Before you specify the model, you will need to compute an interaction variable.
A. The interaction variable is computed by multiplying ____________times _____________.
B. Which of the following groups of respondents will have a value of 0 on the interaction variable?
i) Catholic low-attenders
ii) non-Catholic low-attenders
iii) Catholic high-attenders
iv) non-Catholic high-attenders
C. Which of the following groups of respondents will have a value of 1 on the interaction variable?
i) Catholic low-attenders
ii) non-Catholic low-attenders
iii) Catholic high-attenders
iv) non-Catholic high-attenders
D. Write out the interaction model to be estimated.
E. Focus on the coefficient that estimates the interaction effect. If your idea is correct – that the positive effect of religious attendance on anti-abortion attitudes is significantly stronger for Catholics than non-Catholics – then would you expect the sign on the coefficient to be:
i) negative
ii) positive
iii) close to 0

## Each of the following conclusions is based on a relationship between X and Y

Each of the following conclusions is based on a relationship between X and Y that could be spurious. For each one: (i) Identify a plausible control variable, Z. (ii) Briefly describe how Z might be affecting the relationship between X and Y.
A. The level of ice cream sales (X) and crime rate (Y) are strongly related: As sales go up, so does the crime rate. Conclusion: To reduce the crime rate, ice cream should be prohibited.
B. When one looks at the relationship between marital status (X) and party identification (Y), one finds: Married people are more likely to be Republican than people that are not married. Conclusion: Getting married causes people to become Republican.
C. Individuals’ attendance at religious services (X) is related to the number of children they have (Y). Conclusion: Declining religious attendance causes declining birthrates.

## Explain a linear relationship without references to a graph

2. Explain a linear relationship without references to a graph.
3. Explain the difference between reliability and validity of measurements. Elaborate.
4. When is it appropriate to use comparison of means instead of crosstabulation?

## Robert Putnam’s research has stimulated interest

Robert Putnam’s research has stimulated interest in the role played by voluntary associations in American democracy. Putnam’s work seems to suggest that, when people get involved in groups and help make collective decisions for the group, they develop participatory skills. These participatory skills, in turn, cause people to participate more in politics – voting at higher rates than people who are not involved in any groups.
A. This explanation says that the causal relationship between the independent variable and the dependent variable is mediated by an intervening variable.
The independent variable is?
The dependent variable is?
The intervening variable is?
B. Based on the explanation, write a hypothesis in which the intervening variable is the dependent variable.
C. Based on the explanation, write a hypothesis in which the intervening variable is the independent variable.

## Index Construction and Use SPSS

Homework 5: Index Construction & Use Comments
This assignment continues a series of labs and homeworks in which you utilize statistical skills for basic
research. For this assignment, you will again manipulate variables and construct a basic index, as you have
done in several earlier assignments. However, for this assignment, you will take an additional step, using the
index that you create for simple bivariate descriptions of the sample. The index will be the “dependent variable”:
Specifically, you will use ordinal measures to compare support for possible explanations of variation in the index.
Instructions
You will be using the data file hw5.sav to examine variation in respondents’ satisfaction with four areas of their
lives (family, friends, finance, and job). You will then create a summary measure of overall satisfaction, and will
explore how (and whether) that summary measure varies in two ways: across educational levels and with
frequency of sexual activity. Finally, you will briefly explore interactions among these possible influences on
satisfaction. (Note that most of the recoding has been done for you – this is not always the case.)
Requirements & Questions
You must submit your output file (complete but cleaned) and typed answers to these questions. Typed. Probably
with a computer, maybe with some other device, possibly a typewriter. But not a pen, pencil, or crayon. Typed.
1. Univariate analyses of component and independent variables:
• Perform a univariate analysis of SATFAM, SATFIN, SATJOB, and SATFRND – For each, you should
look at and briefly summarize the frequency distribution, as well as basic summary statistics for central
tendency and dispersion. Go beyond just reporting the data and say something interesting (here and
below). For example, about which issues are the respondents the most/least happy?
• Look briefly at the distributions of EDUC and SEXFREQ. (Note, in particular, the percent of the sample
who refused to answer or otherwise did not have an answer for SEXFREQ.)
2. Construct and assess index:
• Construct an index (including variable labels and value labels, at least for the extremes), called
HAPPY, as the summation of values for the four components listed above.
• Perform a univariate analysis of HAPPY – look at and briefly summarize the frequency distribution, as
well as basic summary statistics for central tendency and dispersion..
• What is this variable conceptually? What does it measure, and what does it mean? What does it tell us
that the individual components do not?
• Interpret the “alpha” for your index – is the index reliable? is it a good one? why or why not?
3. Bivariate analyses – what makes people happy?
• Using correlations and chi-square, what can you say about the relationship between educational
attainment and overall satisfaction (i.e. between HAPPY and EDUC)? (You will need to request a
crosstab to get chisquare, but ignore the table itself, for now.) Is it strong? statistically significant?
• Using correlations and chi-square, what can you say about the relationship between frequency of
sexual activity and overall satisfaction (i.e. between HAPPY and SEXFREQ)? (You will need to request
a crosstab to get chisquare, but ignore the table itself, for now.) Is it strong? statistically significant?
4. Discussion/conclusions
• What can you infer from these findings about what makes people happy? (Hint: Did either of the two
independent variables (EDUC and SEXFREQ) have a statistically significant effect on the dependent
variable (HAPPY)?)
• Bonus: Put that at a conceptual level, thinking about what broader concepts these variables might
operationalize. Of what larger concept might education be a specific instance, indicator, or aspect?

## Index Construction and Use SPSS

Homework 5: Index Construction & Use Comments
This assignment continues a series of labs and homeworks in which you utilize statistical skills for basic
research. For this assignment, you will again manipulate variables and construct a basic index, as you have
done in several earlier assignments. However, for this assignment, you will take an additional step, using the
index that you create for simple bivariate descriptions of the sample. The index will be the “dependent variable”:
Specifically, you will use ordinal measures to compare support for possible explanations of variation in the index.
Instructions
You will be using the data file hw5.sav to examine variation in respondents’ satisfaction with four areas of their
lives (family, friends, finance, and job). You will then create a summary measure of overall satisfaction, and will
explore how (and whether) that summary measure varies in two ways: across educational levels and with
frequency of sexual activity. Finally, you will briefly explore interactions among these possible influences on
satisfaction. (Note that most of the recoding has been done for you – this is not always the case.)
Requirements & Questions
You must submit your output file (complete but cleaned) and typed answers to these questions. Typed. Probably
with a computer, maybe with some other device, possibly a typewriter. But not a pen, pencil, or crayon. Typed.
1. Univariate analyses of component and independent variables:
• Perform a univariate analysis of SATFAM, SATFIN, SATJOB, and SATFRND – For each, you should
look at and briefly summarize the frequency distribution, as well as basic summary statistics for central
tendency and dispersion. Go beyond just reporting the data and say something interesting (here and
below). For example, about which issues are the respondents the most/least happy?
• Look briefly at the distributions of EDUC and SEXFREQ. (Note, in particular, the percent of the sample
who refused to answer or otherwise did not have an answer for SEXFREQ.)
2. Construct and assess index:
• Construct an index (including variable labels and value labels, at least for the extremes), called
HAPPY, as the summation of values for the four components listed above.
• Perform a univariate analysis of HAPPY – look at and briefly summarize the frequency distribution, as
well as basic summary statistics for central tendency and dispersion..
• What is this variable conceptually? What does it measure, and what does it mean? What does it tell us
that the individual components do not?
• Interpret the “alpha” for your index – is the index reliable? is it a good one? why or why not?
3. Bivariate analyses – what makes people happy?
• Using correlations and chi-square, what can you say about the relationship between educational
attainment and overall satisfaction (i.e. between HAPPY and EDUC)? (You will need to request a
crosstab to get chisquare, but ignore the table itself, for now.) Is it strong? statistically significant?
• Using correlations and chi-square, what can you say about the relationship between frequency of
sexual activity and overall satisfaction (i.e. between HAPPY and SEXFREQ)? (You will need to request
a crosstab to get chisquare, but ignore the table itself, for now.) Is it strong? statistically significant?
4. Discussion/conclusions
• What can you infer from these findings about what makes people happy? (Hint: Did either of the two
independent variables (EDUC and SEXFREQ) have a statistically significant effect on the dependent
variable (HAPPY)?)
• Bonus: Put that at a conceptual level, thinking about what broader concepts these variables might
operationalize. Of what larger concept might education be a specific instance, indicator, or aspect?

## Merger and acquisition engagement of environmental innovators in the automotive industry Software: STATA

Master Level, Use of STATA, Orbis and Zephyr, has to contain patents data, merger and acquisition data, Please use all 3 databases. The paper also requires statistical models such as a regression for example, 4000 words, 15 pages, times new roman 12, i also added my slides and example studies. The assessmentform is also in there which is very important. Please read them to get a picture of the required level

## Merger and acquisition engagement of environmental innovators in the automotive industry Software: STATA

Master Level, Use of STATA, Orbis and Zephyr, has to contain patents data, merger and acquisition data, Please use all 3 databases. The paper also requires statistical models such as a regression for example, 4000 words, 15 pages, times new roman 12, i also added my slides and example studies. The assessmentform is also in there which is very important. Please read them to get a picture of the required level

## Marketing Research – Quantitative Data Analysis

Topic: Marketing Research – Quantitative Data Analysis

A series of (5) separate Homework Assignments requiring the following: – the correct input of data into the SPSS software and evidence of this process in the form of output in a PDF download. – Summarize, organize and present a summary of your statistical output into easily understandable table(s) on one page – presenting the information asked for in the objectives above, and highlight what you think is necessary for your clients to know in the most easily readable manner.

## Marketing Research – Quantitative Data Analysis

Topic: Marketing Research – Quantitative Data Analysis

A series of (5) separate Homework Assignments requiring the following: – the correct input of data into the SPSS software and evidence of this process in the form of output in a PDF download. – Summarize, organize and present a summary of your statistical output into easily understandable table(s) on one page – presenting the information asked for in the objectives above, and highlight what you think is necessary for your clients to know in the most easily readable manner.