# Project #33384 - Statistics

Online Assignment 1 — Public attitudes toward lawyers

Note: Unless otherwise noted, all of these exercises can be done with a minimum of manual labour. The object is to do the exercises as efficiently as possible, using the knowledge you’ve already acquired about SPSS. Much of the work needed for these exercises can be done by brute force, but that approach will take an exceptionally long time.

Exercise A

In this exercise, we want to create a new variable that represents a composite scale capturing overall attitudes toward lawyers. Please follow the instructions and specifications, and answer the questions, below.

Between the variables named “money” and “control” create a composite variable that adds together “nottrust,” “ruthless,” and “money”.

Variable name:        attitude

Variable label:         Overall attitude toward lawyers

Decimal places:       0

1.    Run a frequency distribution for the “attitude” variable, and print the output.

Note: whenever you are asked to print output, you may either:

a.    copy the output from SPSS and paste it into your assignment; or

b.    print from SPSS and attach the output to the assignment.

If you choose option (b), please make sure you label the outputs properly, so that your TA is able to follow what you’ve done.

2.    What is the lowest recorded value for the overall attitude toward lawyers?

3.    What is the highest recorded value for the overall attitude toward lawyers?

4.    How many respondents have composite attitudinal scores equal to, or greater than, 9?

5.    What is the most common composite attitudinal score?

Exercise B

In this exercise, we want to create a new variable that is based on an existing variable. Specifically, we want to take the “educ” variable and make a new variable that breaks the old variable into three categories. The categories are as follows:

Category 1 – Highest level is less than High School Graduate

Category 2 – Highest level is High School Graduate

Category 3 – Highest level is greater than High School Graduate

Please follow the instructions and specifications, and answer the questions, below.

Between the variables named “educ” and “satis” create a new variable that breaks “educ” into the three categories listed above.

Variable name:        educ_3

Variable label:         Highest Completed Level of Education – 3 Categories

Value labels:           use the categories above

Decimal places:       0

1.    Run a frequency distribution for the “educ_3” variable, and print the output.

2.    How many respondents did not complete high school?

3.    What percentage of respondents have a “highest completed level of education” that is greater than high school?

Exercise C

In this exercise, we want to create a string variable for race that has two categories: Caucasian and non-Caucasian. This is the only exercise that requires you to enter data manually.

Please follow the instructions and specifications, and answer the questions, below.

Between the variables named “race” and “age” create a new variable called “caucasian.”

Variable name:        caucasian

Variable label:         Caucasian string variable

Categories:             Caucasian and non-Caucasian

Value labels:           not applicable; remember, it’s a string variable

Decimal places:       not applicable

1.    Run a frequency distribution for the “caucasian” variable, and print the output.

Exercise D

In this exercise, we want to create a new variable that is based on an existing variable. Specifically, we want to create a new variable, which will rank the “age” variable into 4 distinct categories with approximately equal numbers of people in each category. In contrast to Exercise B, in this exercise we will allow the computer to generate the categories.

This is a hard question, so you get a one-word hint: ntiles (not a typo).

After you create the new variable, answer the following questions:

1.    Run a frequency distribution for the new variable, and print the output.

2.    What is the name of the new variable?

3.    What is the age range associated with each rank?

Answer:      Rank        Low                       High

1.             __________         __________

2.             __________         __________

3.             __________         __________

4.             __________         __________

4.    What % of respondents are in the third rank for age?

Exercise E

We want to look at your dataset. To let us do that, please do the following:

1.    Sort your dataset to that it is arranged from the smallest to the largest Identification Number.

2.    While you are looking at your dataset on the screen, press the Print Screen key. On most computers, this key has “Prnt Scrn” on it. Your computer may be a bit different. Pressing this key does not actually print, but rather, causes the computer to capture an image of whatever is on the screen at the time.

3.    Go to your online assignment file, or to a new word processing page, and paste the screen image into your file. This is your answer for Exercise E.

4.    Save the changes you’ve made to your file. You may want to save the file as a new name, do distinguish it from the old file (in the event you’ve made any mistakes).

 Subject Mathematics Due By (Pacific Time) 06/17/2014 11:00 am
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