Reference no: EM132314856

Analysis Report

Overall Summary of Requirements:

You will again use the 2001 Australian Electoral Study. For Report 2, you will determine how various demographic differences influence punitive attitudes to crime.

• Your report will involve presenting and interpreting a series of bivariate analyses and a multivariate OLS regression analysis.
• You should use tables and/or graphs (as appropriate)
• When possible, present results in one table instead of several.
• Make sure you carefully examine the feedback provided on your first assessment item because some of that may be applicable here.
• Submit your SPSS output (not included in word count) as a separate document under Part 2.

Formatting and Submission is very similar to that in Assessment 1:

Your report must be double-spaced with 11 or 12 point standard font.

Consider this report to be similar to a continuation/elaboration of Analysis Report 1 - you will not have an introduction in this Assessment and you've already described the data source so there is no need to repeat here.

Your report must be formatted as below with required information placed under correct headings. Heading titles should be presented EXACTLY as shown. The headings are the ones in BOLD. Do not include more or less headings than what is listed. Do not change headings in any way. Headings assist with proper marking. DO NOT INCLUDE A COVER PAGE or anything else not specifically listed below. Do not place your name on the paper. TurnItIn places your name on the submission.

Community Attitudes on Crime and Justice in 2001
• Just copy this exact title; don't change it.
• Place the executive summary below this title on the same page.
Executive Summary {1 to 2 paragraphs - ½ to 1 page maximum}
• Write this in a manner similar to Assessment 1 but summarise this assessment instead.
• Make sure you examine Assessment 1's feedback for any hints/suggestions.

Measuring Punitiveness
• Create an additive index that measures punitive attitudes, using the variables e4deathp, e4lawbrk, and e4asylum.
• Before adding together these variables, recode any "reverse coded" questions/items as appropriate. In other words, make sure that high values on each variable represent more punitiveness and not less punitiveness.
• Report and interpret the internal consistency of this index using Chronbach's alpha.

HINTS:

• Make sure you check the codebook for what each question/variable/score means so that you can reverse the coding on "reverse-coded questions" as necessary.
• Make sure you use the original versions of e4deathp, e4lawbrk, and e4asylum that have 5 answer categories even if you collapsed these 5 in some way for Assessment 1.
• If each of the 3 variables has answer categories that go from 1 to 5, then adding all three together will result in a scale/index that ranges from 3 to 15 (assuming that all questions were answered by all respondents). You should check this with descriptives to make sure)

Demographic Characteristics
• You will use the following variables for all analyses: gender, age and home ownership.
• Recode gender as 0=male and 1=female.
• Recode home ownership into own a home = 1 and all other options = 0.
• Use the pre-calculated Age interval-level variable.
• Briefly describe the variables and how they are coded for this report.
• Describe their summary statistics (distributions or means as appropriate).
• Do not make this section more difficult than necessary. You can describe most of these variables in just 1-3 sentences each.

Bivariate Analyses
Present and interpret the bivariate relationships between your punitive index and:
• Gender
• Age
• Home Ownership

Choose the appropriate statistical technique to examine whether enough evidence exists to generalise the relationship from your sample to the population. In other words, use a T-Test, ANOVA, or Correlation as appropriate. Briefly describe the technique and its purpose. You may use sub-headings if you wish.

Make sure you:
• Interpret results
• Present results in an appropriate way
Multivariate Analysis
• Run a single OLS regression where you regress your punitive index on the independent variables; gender, age and home ownership.
• Present and interpret the unstandardized and standardised regression coefficients (b, and B) and their p values; R-squared, and the other OLS results discussed in course content.
• Present the results in a table and interpret in your narrative.

Conclusion
• Summarise your key findings. Focus primarily on the multivariate analysis.

• In other words, what are your more important conclusions about the influence of gender, age and home ownership on punitiveness?

• You can have some reputation of the multivariate analysis here, but just focus on explaining what the most important findings were and why rather than simply repeating the findings.

• This section should not be very long.

Attachment:- instructions.rar