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  • SPSS Survival Manual - Practice Exercises

Open University Press

SPSS Survival Manual: Data files & exercises

Practice exercises.

Each part below contains practice exercises and review questions for each chapter in SPSS Survival Manual .

Part One: Getting started

Part Two: Preparing the data file

Part Three: Preliminary analyses 

Part Four: Statistical techniques to explore relationships among variables

Part Five: Statistical techniques to compare groups

spss homework answers

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  • Stem and Leaf
  • Normality Tests (Anderson-Darling, Kolmogorov)
  • Standard Deviation
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  • t-test, two independent samples, paired samples
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  • ANCOVA and MANOVA in SPSS
  • Levene's Test
  • Chi Square Tests
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Essentials of Social Statistics for a Diverse Society, 3e

Student resources, spss exercises.

Demonstration 1: Producing a One-Sample T Test

            In this chapter, we discussed methods of testing differences in means between a sample and a population value. SPSS includes a One-Sample T Test procedure to do this test. SPSS does not compute the test with the Z statistic; instead, it uses the t statistic to test for all mean differences. The One-Sample T Test procedure can be found under the Analyze menu choice, then under Compare Means, where it is labeled One-Sample T Test. The opening dialog box (Figure 8.1) requires that you place at least one variable in the Test Variable(s) box. Then a test value must be specified.

            We’ll use the GSS2014-B data set for this demonstration. The standard workweek is thought to be 40 hr, so let’s test to see whether American adults work that many hours each week. In this example, place HRS1 in the Test Variable(s) box and “40” in the Test Value box. Then click on OK to run the procedure.

Figure 8.1.  One-Sample T Test Dialog Box

Chapter 8_1

            The output from the One-Sample T Test procedure is not very extensive (see Figure 8.2). A total of 895 people answered the question about number of hours worked per week. The mean number of hours worked is 41.47, with a standard deviation of 15.039. Below this, SPSS lists the test value, 40. It includes the two-tailed significance, or probability, for the one-sample test. This value is .004, given the calculated t statistic of 2.918, with 894 degrees of freedom. Thus, at the .01 significance level, we would reject the null hypothesis and conclude that American adults work more than 40 hr/week.

            SPSS also supplies a 95% confidence interval for the mean difference between the test value and the sample mean. Here, the confidence interval runs from .48 to 2.45, providing estimates of how much more than 40 hr/week Americans work.

Figure 8.2.  One-Sample T Test Output

Chapter 8_2

Demonstration 2: Producing a Test of Mean Differences

            In this chapter, we have also discussed methods of testing differences in means or proportions between two samples (or groups). The Two-Sample T Test procedure can be found under the Analyze menu choice, then under Compare Means , where it is labeled Independent-Samples T Test .

            The opening dialog box requires that you specify various test variables (the dependent variable) and one independent or grouping variable (Figure 8.3). We’ll test the null hypothesis that men and women work the same number of hours each week by using the variable HRS1. Place that variable in the Test Variable(s) box and SEX in the Grouping Variable box. When you do so, question marks appear next to SEX indicating that you must supply two values to define the two groups (independent samples). Click on Define Groups . Then put “1” in the first box and “2” in the second box (1 = male and 2 = female ), as shown in Figure 8.4. Then click on Continue and OK to run the procedure.

Figure 8.3.  Independent-Samples T Test Dialog Box

Chapter 8_3

Figure 8.4.  Define Groups Dialog Box

Chapter 8_4

            The output from Independent Samples T test (Figure 8.5) is detailed and contains more information than we have reviewed in this chapter. The first part of the output displays the mean number of hours worked for Whites and Blacks, the number of respondents in each group, the standard deviation, and the standard error of the mean. We see that males worked 5.00 hr more per week than females (43.92 – 38.92 = 5.00).

Figure 8.5.  Independent-Samples T Test Output

Chapter 8_5

            Earlier in the chapter, we reviewed the Levene’s Test and how to determine whether the variances of the two groups are equal. In this case, we reject the null hypothesis of equal variances (the significance of F is .027 < .05 α). The t obtained is 5.048 (equal variances not assumed) with a probability of .000 (smaller than .05 or .01). We can reject the null hypothesis of no difference and conclude that men work significantly more hours per week than women. The difference of 5.00 hr is significant at the .000 level.

            What if we wanted to do a one-tailed test instead? SPSS does not directly list the probability for a one-tailed test, but it is easy to calculate. If we had specified a directional research hypothesis--such as that men work more hours than women--we would simply take the probability reported by SPSS and divide it into half for a one-tailed test. Because the probability is so large in this case, our conclusion will be the same whether we do a one- or a two-tailed test.

            The last portion of output on each line is the 95% confidence interval for the mean difference in hours worked between the two groups. (Confidence intervals were reviewed in chapter 7.) It is helpful information when testing mean differences because the actual mean difference will vary from sample to sample. The 95% confidence interval gives us a range over which the sample mean differences are likely to vary.

SPSS Problems [GSS14SSDS-B]

1. Use the GSS file to investigate whether or not Americans use the Internet at least 7 hr per week (estimating an hour per day). Perform the One Sample T Test procedure (as presented in SPSS Demonstration 1) to do this test with the variable WWWHR. Do the test at the .01 significance level. What did you find? Do Americans use the Internet 7 hr per week, more or less?

2. The GSS includes a measure of highest educational degree completed (DEGREE). Test whether there is a significant difference between those with less than high school (coded 0) and those with a bachelor’s degree (coded 3) in the number of hours on the Internet per week (WWWHR). Assume α is .05 for a two-tailed test. Summarize your findings.

3. Investigate the difference between individuals who support legalization of marijuana from those who do not based on data from the GSS. Use the variable PRES12 as your independent or grouping variable (1 = Obama and 2 = Romney). Investigate whether there is a significant difference between these two groups in terms of their age (AGE), education (EDUC), and respondent income (NRINCOME06). Assume that α is .05 for a two-tailed test. Based on your analysis, write three Step 5–type statements summarizing your findings.

4. For this analysis, use the variable GOD as your independent variable, comparing individuals who believe in some higher power (3) or know God exists (6). Use the same dependent variables, AGE, EDUC, and NRINCOME06, to estimate t- tests. Assume α is .05 for a two-tailed test. Prepare a statement to summarize your findings.

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What Is SPSS? What Are Its Key Features And Uses/Applications

SPSS, short for the Statistical Package for the Social Sciences, is not just software; it's the secret decoder for the language of data. Crafted by IBM, SPSS is a tool preferred by researchers, statisticians, and analysts for its prowess in dissecting and making sense of data across various fields. Initially tailored for social science pursuits, SPSS finds its applications across diverse domains today. 

Key Features:

  • SPSS, with its user-friendly interface, transforms complex data analysis into an accessible journey. Navigating data import, cleaning, and manipulation becomes a breeze, especially for those new to statistical analysis. 
  • Its comprehensive set of statistical procedures, ranging from basic descriptive statistics to advanced analyses caters to users with varying expertise levels. 
  • SPSS goes beyond historical data examination, delving into predictive analytics. Techniques like linear regression and decision trees allow users to construct and assess predictive models, adding a forward-looking dimension to data analysis. 
  • Customization options and automation features bring flexibility, making SPSS a dynamic tool for tailored analyses and efficient workflows. Lastly, its robust reporting capabilities weave together statistical results, tables, and charts, simplifying findings presentation for clearer insights.

Uses/Applications:

  • In the world of psychology, sociology, and political science, SPSS aids researchers in deciphering nuanced data patterns and extracting meaningful insights. 
  • Market researchers find SPSS a guiding light, unraveling consumer behavior, interpreting survey data, and guiding businesses with informed decision-making.  Healthcare researchers lean on SPSS for clinical studies and epidemiological research.
  • Finance and banking sectors harness SPSS for robust financial analysis, risk assessment, and fraud detection, providing a data-driven compass for strategic decisions.  
  • Government agencies rely on SPSS for evidence-backed policy decisions, demographic analyses, and a deeper understanding of societal trends.

SPSS is not just a tool; it's the companion guiding researchers and analysts enabling them to navigate the journey of analyzing data and turning it into meaningful insights. 

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Our experts at The Statistics Assignment Help cover a comprehensive array of topics to ensure a holistic understanding and mastery of SPSS for your assignments and homework.

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  • Correlation Analysis: Examination of relationships between variables through correlation analysis, utilizing tools within SPSS.
  • Chi-square Tests : Application of chi-square tests to analyze categorical data and assess associations between variables.
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  • Cluster Analysis: Exploration of cluster analysis techniques to identify natural groupings within datasets.
  • Time Series Analysis : Application of time series analysis to study patterns and trends within data over time.
  • Multivariate Analysis of Variance (MANOVA): Understanding and implementation of MANOVA to analyze the differences between groups across multiple dependent variables.
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  • Race Against Time: Student life is a whirlwind, and deadlines are like tornadoes. Balancing SPSS assignments with other commitments can be a real challenge, leaving students wishing for a bit more time.
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Popular Student Queries While Solving Spss Homework & Assignments?  

How do I Input and Sort Data in SPSS?  Many students find themselves scratching their heads when it comes to putting data into SPSS and making sure it's organized properly. They often seek clear guidance on data input methods, handling missing values, and ensuring accuracy for a smooth analysis.

I'm Stuck Choosing a Statistical Test. Can You Help Me Decide? Navigating through the array of statistical tests can be a daunting task, leaving students in a state of uncertainty about the most suitable choice. Frequently, they seek guidance to determine the optimal statistical test for their data – whether it involves t-tests, ANOVA, or regression – all with the goal of ensuring precision in their analysis.

Deciphering SPSS Output Feels Like a Puzzle. Any Clues? Interpreting the results from SPSS can be akin to solving a mystery. Students frequently express confusion about the significance of statistical output and seek help in unraveling the meaning behind the numbers and charts for a better understanding.

Creating Visuals in SPSS is Tricky. Any Tips for Clear Graphs? Converting raw data into visually engaging graphs and charts presents a considerable challenge. Students frequently seek support to craft visually captivating depictions of their data, aiming not only for accuracy in their findings but also for a presentation that is coherent and easily understood.

SPSS Syntax Seems Like a Different Language. Can You Break it Down? The language of SPSS syntax can feel foreign to students. They frequently request explanations and support in using SPSS syntax to perform advanced analyses, automate tasks, and make their SPSS journey less daunting. Addressing these genuine queries ensures that students receive personalized support, making their SPSS learning experience more accessible and enjoyable.

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What is SPSS?

SPSS is an acronym for Statistical Package for the Social Sciences in its full form. It is well-known in the field of statistics and in a variety of other markets; nevertheless, it has also made a name for itself in the field of health sciences.

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