Day 4 trouble-shooting. SPSS

M. Amir Hossain Ph.D.

Professor

ISRT, University of Dhaka

Day-4_Trouble Shooting

M. Samsul Alam

Lecturer


Problem 1

We have a small data set containing information on some 15 hospital patients who came for their

regular check up. Systolic blood pressure (SBP), identification number (ID), age, gender, years of

schooling (Year_S), monthly income, and the place of residence of these patients are recorded.

ID SBP Age Sex Year_S Income Residence

1 130 25 M 4 3000 U

2 140 48 F 6 5000 R

3 160 50 M 8 5000 SU

4 160 47 M 12 6500 R

5 141 30 F 10 6000 R

6 144 37 M 11 6000 SU

7 155 26 F 8 6300 R

8 129 22 M 3 2500 U

9 164 51 F 5 2500 R

10 124 16 F 5 2400 SU

11 125 29 F 10 4500 U

12 136 32 M 12 8000 U

13 125 25 F 12 7500 R

14 126 28 M 14 14000 R

15 165 55 M 14 16000 SU

Here, M = Male, F = Female; U = Urban; R = Rural; SU= Semi-urban.

(a) Entry the above data in SPSS for the purpose of analysis. What can we do to make the

variables and values of the string variable more understandable to others? Perform these

operations if any.

(b) Here we see that different patients have different incomes. Instead of analyzing their

incomes numerically we are interested to classify them in some income groups according to

their incomes without changing the original variable. Create a new variable representing the

different income groups with appropriate value and variable labels.

(c) For different computational problems string variables may cause some problems that can be

avoided if these are replaced by the numeric ones. Convert the available string variables in

your data into numeric variable and also give the value and variable label.

(d) For some additional analysis we want a new data set which contains the variables ID, SBP,

SEX, and INCOME. Save this SPSS formatted data file in a suitable drive of your PC. Also

save the data file in MS Excel format keeping these same variables.


Professor



M. Samsul Alam

Lecturer


Problem 2

A SPSS formatted dataset ‘Car.sav’ is given. There are eight variables giving information on some

406 cars namely mpg (Miles per Gallon), engine (Engine Displacement in cubic inches), horse

(Horsepower), weight (Vehicle Weight in lbs.), accel (Time to Accelerate from 0 to 60 mph in

seconds), year (Model Year), origin (Country of Origin), and cylinder (Number of Cylinders).

Answer the followings:

(a) Instead of representing model in year we may be interested in type of model which is

defined as follows:

Type of Model Model Year

Old 70-75

Modern 76-80

Ultramodern 81-82

Now create a new variable which defines the type without altering the original year variable

according to the above instruction.

(b) Create a variable n_origin from existing variable origin where the values of origin 1, 2, 3

are replaced by 10, 20, and 30 respectivly.

(c) Compute a new variable named hiwgt whose value is ‘good’ if weight is more than 3000 lb.

(d) Find out the price (variable name should be price) of the car if the price is determined on

the basis of the number of cylinders given as follows:

(e) Additionally $500 more to be added to the cars with horsepower > 100. Now calculate the

final price of the cars creating a new variable with the consideration of this additional price.

(f) From the given dataset ‘Cars’ create the following datasets using the sub setting conditions

given below and save them all in D drive of your computer:

Name of data set Sub setting Conditions

amercar only for origin: America

japcar only for origin: Japanese

Cyl4 For cylinder = 8 and Keep variables mpg, engine,

horse, and weight

Number of cylinders in car Price

3 $ 10,000

4 $ 12,000

5 $ 14,000

6 $ 16,000

8 $ 18,000


Professor



M. Samsul Alam

Lecturer


Problem 3

a) Two data sets Anxiety1.sav and Anxiety2.sav contain information of six trials performed

on twelve subjects. The first data set containing the information on first four trial and the

other data set containing the remaining. Merge these two data set and save the new data as

Anxiety.sav.

b) The Anxietya.sav file containing information on few variables from 30 individuals whereas

the Anxietyb.sav file containing information on the same variables but from another 18

individuals. Append the data to obtain a single data file that will contain information of all

the 48 individuals.

Problem 4

A SPSS formatted dataset ‘Demo.sav’ is given. There are eight variables giving information on

some 6400 cases namely age (age in years), income (household income in thousands), inccat

(income category in thousands), car (price of primary vehicle), carcat (primary vehicle price

category), jobsat (job satisfaction), gender (gender) and reside (number of people in household).

Answer the followings:

(a) Draw a bar chart of mean income with carcat and mean income with jobsat. Comment on

the result.

(b) Draw histogram of age and income with normal curve. Comment on the result.

(c) Draw a pie chart of reside.

(d) Draw boxplot of income for gender. Can we use arithmetic mean to calculate the average

income for gender?

(e) Make frequency table for age, taking class interval 10 starting from age 18. Also find the

mean, median, mode, quartiles, 90th

percentile and standard deviation.

Problem 5

Glaucoma is a leading cause of blindness in the US. The following table gives the measurement of

the corneal thickness, in microns, of eight patients who had glaucoma in one eye but not in the

other.

Patient Normal Glaucoma

1

2

3

4

5

6

7

8

484

478

492

444

436

399

464

476

488

479

480

426

440

410

458

460

At the 10% level of significance, do the data provide sufficient evidence to conclude that mean

corneal thickness is greater in normal eyes than in eyes with glaucoma?


Professor



M. Samsul Alam

Lecturer


Problem 6

A corporation is trying to decide which of the three makes of automobile to order for its fleet-

domestic, Japanese, or European. Five cars of each type were ordered, and after 10,000 miles of

driving, the operating cost per mile of each was assessed. The accompanying results in cents per

mile were obtained.

Domestic Japanese European

18.0

17.6

15.4

19.2

16.9

20.1

15.6

16.1

15.3

15.4

19.3

17.4

15.1

18.6

16.1

(a) Set out the analysis of variance table.

(b) Test the null hypothesis that the population mean operating costs per miles are the same for

these three types of cars.

Problem 7

Using the data ‘hsb.sav’ solve the following problems.

(a) Suppose that the general population consists of 10% Hispanic, 10% Asian, 10% African

American and 70% White folks. Test whether the observed proportions from our sample

population differ significantly from these hypothesized proportions?

(b) Test whether there is any association between the type of school attended and the student’s

gender? Also test whether there is any association between the student’s gender and their

socio-economic status?


Professor



M. Samsul Alam

Lecturer


Problem 8

Do the subsequent tasks using SPSS based on the following sample questionnaire:

a) Construct a SPSS data entry layout for the questions listed in the given sample

questionnaire with suitable variable names and description.

b) Add appropriate value labels for the variables when required.

c) Specify the scale of measurements for all the variables.

d) Assign user defined missing values for every variable.

e) Change the settings so that the data view window will show the value labels.


Professor


Day 4: Second Session Trouble Shooting: I

M. Samsul Alam

Lecturer


Education

Day 4 trouble-shooting. SPSS