Data File Management and Descriptive Statistics with SPSS: Describing the Sample Demographics and Key Variables

Using the information that you computed in Chapters 4 and 5, we can now describe this sample of the High School and Beyond (hsb) data. In an article or research report such as a thesis, you will, at a minimum, state the number of participants and provide summary information about the age, gender, and ethnicity characteristics of the sample. We do not have age as a variable in this data set; all the participants were high school seniors and are assumed to be about 18 years old. We do have gender and ethnicity. For a more complete description of sample demographics, we will add mother’s and father’s education (revised). This information probably would be described in the Methods section of an article or thesis and could include a table as shown in the box labeled How to Write about Sample Demographics. The data for gender and ethnicity are found in Output 4.5; the revised mother’s education and father’s education frequencies are found in Output 5.2. Note that there is always text preceding a table and that the text highlights and often simplifies the material in the table; never repeat everything in the table or include a table without referring to it in the text.

How to Write About Sample Demographics

Method

Participants

Data from 75 high school seniors (34 males and 41 females) were gathered. The majority of the group (54.7%) was of European American ethnicity. Table 1 shows the frequencies and percentages of students by gender, ethnicity, and parent education. Note that data on education were missing for two fathers. Percentages for Father’s Education refer to percentage of those for whom data are available. Most of the mothers (64%) and fathers (52.1%) had a high school education or less. Approximately 26% of the fathers but less than 11% of the mothers had a bachelor’s degree or more.

Table 5.1

Demographics of a Sample of 75 High School Seniors

The results section of a research report or thesis will often provide descriptive data and, perhaps, a table about the key variables in the study. This description of the variables may, but likely will not, directly address the research questions for the study. Several key variables, whether or not students had taken each of five types of mathematics courses and how they performed in all their math courses, were dichotomous. Other key variables, such as various test scores and attitudes about mathematics, were essentially continuous and most were approximately normally distributed. In the box labeled How to Describe Key Variables, we show one way to describe the variables and summarize them in tables. The data for math courses taken and grades come from Output 4.4. The data on the test scores and math attitudes come from Outputs 4.1b and 5.5.

Note that means, standard deviations, and skewness are all rounded to two decimal places and right justified. Statistical symbols with English letters (e.g., N, n, M, SD) are italicized in the text and tables.

How to Describe Key Variables

Results

Table 5.2 shows the number and percentage of the 75 high school seniors who had taken each of five mathematics courses. More than three-fourths of them (79%) had taken algebra 1. Approximately half had taken algebra 2 (47%) and/or geometry (48%), but only 27% had taken trigonometry and relatively few (11%) had taken calculus. Although not shown in Table 5.2, 41% were judged to have high math grades (As and Bs), and 59% had low math grades.

Table 5.2

Means, standard deviations, and skewness of eight key variables are shown in Table 5.3. The four achievement test scores vary widely in means and SDs given differences in scale, but all are approximately normally distributed. The three mathematics attitude scales have means of approximately 3 on 1 – 5 rating scales; the average motivation scale ratings are somewhat lower than those for the students’ perceived competence and pleasure with math. Note that the competence ratings are quite highly skewed. On the average students took 2.11 math courses.

Source: Morgan George A, Leech Nancy L., Gloeckner Gene W., Barrett Karen C.

(2012), IBM SPSS for Introductory Statistics: Use and Interpretation, Routledge; 5th edition; download Datasets and Materials.