| student_id | age | gender | dept | class_attentive | mobile_disrupt | height_cm | weight_kg | socio_econ |
|---|---|---|---|---|---|---|---|---|
| 1 | 19 | 1 | 5 | 1 | 3 | 170.3 | 64.5 | 2 |
| 2 | 20 | 2 | 4 | 0 | 1 | 152.6 | 46.5 | 1 |
| 3 | 22 | 2 | 5 | 1 | 1 | 172.8 | 74.4 | 1 |
| 4 | 19 | 2 | 5 | 1 | 2 | 148.3 | 47.4 | 3 |
| 5 | 19 | 1 | 3 | 0 | 3 | 155.8 | 47.4 | 2 |
| 6 | 20 | 1 | 5 | 1 | 1 | 171.3 | 61.7 | 1 |
Assignment 1: Working with Data in SPSS
(PSY206) Data Management and Analysis
Instructions
You are provided with the dataset: class_data.xlsx (Click to download)
Download the data and complete the tasks using SPSS. Submit both the data (.sav) and the output (.spv) files in the designated classroom thread.
Data Overview
The dataset represents information collected from 50 undergraduate students of a university during a classroom survey on learning environments and attention levels. The purpose of the survey was to understand whether different demographic, psychological, and environmental factors influence students’ concentration in class.
The survey includes:
- Basic demographic information such as age, gender, and department
- Physical measurements (height and weight) for calculating BMI
- Class attentiveness, indicating whether the student remains attentive during lectures
- Whether mobile phone usage causes class disruption
- Socioeconomic background of students, self-reported on a three‐category scale
All identifying information has been removed and responses are coded numerically for data analysis.
Data Head
Variable Coding Instructions
| Variable | Codes & Value Labels |
|---|---|
| gender | 1 = Male, 2 = Female |
| dept | 1 = Statistics, 2 = Nutrition, 3 = Physics, 4 = Psychology, 5 = Mathematics |
| class_attentive | 1 = Yes, 0 = No |
| mobile_disrupt | 1 = Yes, 2 = No, 3 = Sometimes |
| socio_econ | 1 = Low, 2 = Middle, 3 = High |
Question 1 — Data Import and Setup
- Import the file
class_data.xlsxinto SPSS
- In Variable View, properly define the following:
- Variable labels
- Value labels for categorical variables
- Measurement scale (Nominal, Ordinal, Scale)
- Other properties (if applicable)
- Save the file as
class_data.sav
Question 2 — Data Exploration
Generate the following outputs in SPSS:
- Frequency tables for:
- gender
- class_attentive
- mobile_disrupt
- A bar chart showing the distribution of class attentiveness
- Descriptive statistics (Mean, SD, Minimum, Maximum) for:
- age
- height (cm)
- weight (kg)
Question 3 — Data Management
Perform the following data transformations:
-
Compute BMI:
\[BMI = \frac{weight\_kg} {(height\_cm/100)^2 }\]
-
Create a new variable
BMI_Status(Categorical):- Underweight: BMI < 18.5
- Normal: 18.5 \(\le\) BMI \(\le\) 25
- Overweight: BMI \(\ge\) 25
Run a frequency table for the newly created BMI Status variable
- Underweight: BMI < 18.5
-
Recode
mobile_disruptto binary variable:- Not Disruptive = No
- Disruptive = Yes / Sometimes
Create a bar chart showing the distribution of the recoded Mobile Disruption variable (Disruptive vs Not Disruptive).
- Not Disruptive = No
Sort the dataset by height in descending order and then by BMI in descending order.
Split file by gender and run attentiveness frequency separately