Cj 301 Independent Project 1 Univariate Analysis Chapter 4 S

Question

Cj 301independent Project 1univariate Analasys Chapter 4 Spssdue Dat Cj 301 independent Project 1 UNIVARIATE ANALASYS: CHAPTER 4- SPSS Due date: March 22 – Sunday by midnight 20 Points PLEASE BE CAREFUL: THERE ARE 2 PARTS Please recode the variable AGE into a new variable called AGE2 with categories for: · Teens · Twenties · Thirties and so on. Be sure to include the new variable labels for AGE2. Request a frequency chart for AGE2 and answer the following questions: 1. How many respondents are in their forties? 2. What percentage is under fifty? 3. Which category has the fewest cases? Instructions: When recoding AGE into AGE2, first perform a frequency distribution to examine all valid AGE values. Assign categories as follows: - Teens: 0–19, value 1 - Twenties: 20–29, value 2 - Thirties: 30–39, value 3 - Forties: 40–49, value 4 - Fifties: 50–59, value 5 - Sixties: 60–69, value 6 - Seventies: 70–79, value 7 - Eighties: 80 and above, value 8 Any other values should be coded as system missing. After creating AGE2, define variable and value labels, remove decimals, and verify the labels and coding. In the second part, request frequencies for the variable CHLDIDEL (ideal number of children). Record the minimum, maximum, mode, total respondents, mean, and standard deviation based on SPSS output. Ensure to follow the procedural steps as described in Chapter 4 of your textbook, including recoding, labeling, and cleaning data. Save the dataset once completed for future use. ---

Dr. Jack HW Helper · Accepted Answer

Cj 301independent Project 1univariate Analasys Chapter 4 Spssdue Dat Introduction Understanding univariate data is fundamental in statistical analysis, especially in exploring survey datasets such as the General Social Survey (GSS). This assignment focuses on applying SPSS to execute data recoding, labeling, frequency analysis, and descriptive statistics. Through these procedures, we interpret respondents’ age categories, identify distribution characteristics, and analyze respondents' ideal number of children, aiding in comprehending demographic patterns and attitudes within the dataset. Part 1: Recoding Age into Age2 The initial step involves examining the age variable within the GSS dataset. Performing a frequency distribution allows for understanding the range and valid values of age data, excluding missing responses. Based on these values, recoding transforms the continuous age variable into a categorical variable, AGE2, with clearly defined age groups. The categories were assigned as follows: - Teens (0–19): coded as 1 - Twenties (20–29): coded as 2 - Thirties (30–39): coded as 3 - Forties (40–49): coded as 4 - Fifties (50–59): coded as 5 - Sixties (60–69): coded as 6 - Seventies (70–79): coded as 7 - Eighties (80 and above): coded as 8 The recoding process required setting non-conforming values to system missing, verifying categories, and ensuring labels were appropriately assigned. Variable labels, such as "Age Categories," were added for clarity, and value labels for each category ("Teens," "Twenties," etc.) were also assigned. Once recoded, the variable's decimal places were set to zero for clarity. The variable label was updated to improve interpretability, and the value labels were checked to confirm accurate mapping. The frequency chart for AGE2 provides distribution insights, including the number of respondents in each age category and percentages. From the output, responses in the forties were identified, and the proportion under fifty calculated, show

Cj 301 Independent Project 1 Univariate Analysis Chapter 4 S

Cj 301independent Project 1univariate Analasys Chapter 4 Spssdue Dat

Paper For Above instruction

Introduction

Part 1: Recoding Age into Age2

Part 2: Descriptive Statistics for Ideal Number of Children (CHLDIDEL)

Conclusion

References