10.2 Examples of APA-Style Results

In this section, we will look at examples of APA-style results for several statistical tests. You may not have learned all of these tests yet, and that is okay. The goal here is to show the writing pattern.

The test-specific chapters later in the book will give more detailed guidance for each analysis.

Example: Independent Samples t-Test

Let’s walk through an example using an independent samples t-test.

Here are the four pieces of information we need:

  1. Research question or hypothesis: Is there a difference in student grades between Anastasia’s and Bernadette’s classes?
  2. Descriptive statistics: Anastasia’s students (M = 74.53, SD = 9.00, n = 15); Bernadette’s students (M = 69.06, SD = 5.77, n = 18)
  3. Inferential statistics: t(31) = 2.12, p = .043, d = .74
  4. Interpretation: Anastasia’s students had significantly higher grades than Bernadette’s students.

APA-style write-up

The research question was whether there was a difference in student grades between Anastasia’s and Bernadette’s classes. Anastasia’s students (M = 74.53, SD = 9.00, n = 15) had significantly higher grades than Bernadette’s students (M = 69.06, SD = 5.77, n = 18), t(31) = 2.12, p = .043, d = .74.

Let’s compare that write-up against the four things we need to report:

#1: The research question was whether there was a difference in student grades between Anastasia’s and Bernadette’s classes. #2 and #4: Anastasia’s students (M = 74.53, SD = 9.00, n = 15) had significantly higher grades than Bernadette’s students (M = 69.06, SD = 5.77, n = 18), #3: t(31) = 2.12, p = .043, d = .74.

Alternative formatting

Sometimes, authors place statistical information in parentheses. In this case, use brackets for degrees of freedom because we cannot place parentheses inside parentheses.

I tested the difference in grades between Anastasia’s students (M = 74.53, SD = 9.00, n = 15) and Bernadette’s students (M = 69.06, SD = 5.77, n = 18). An independent samples t-test showed that Anastasia’s students had significantly higher grades than Bernadette’s students (t[31] = 2.12, p = .043, d = .74). Therefore, we rejected the null hypothesis that there was no difference in grades between the two classes.

The first version is a little more concise. The second version separates the research question, test result, and decision more clearly. Both can work.

Example: Chi-Square Test of Independence

A chi-square test of independence is used when we want to know whether two categorical variables are associated.

Here are the pieces of information we need:

  1. Research question: Is tutoring attendance associated with pass/fail status?
  2. Descriptive statistics: Frequencies and percentages for pass/fail status by tutoring attendance
  3. Inferential statistics: χ²(1, N = 120) = 6.42, p = .011, Cramer’s V = .23
  4. Interpretation: Students who attended tutoring were more likely to pass than students who did not attend tutoring.

APA-style write-up

I examined whether tutoring attendance was associated with pass/fail status. Students who attended tutoring were more likely to pass (42 of 50, 84.0%) than students who did not attend tutoring (45 of 70, 64.3%). A chi-square test of independence showed that tutoring attendance and pass/fail status were significantly associated, χ²(1, N = 120) = 6.42, p = .011, Cramer’s V = .23.

Why this works

This write-up includes the research question, the frequencies and percentages, the inferential test result, the effect size, and a plain-language interpretation. For chi-square tests, the descriptives are usually counts and percentages rather than means and standard deviations.

Example: Correlation

A correlation is used when we want to examine the association between two continuous variables.

Here are the pieces of information we need:

  1. Research question: Is time spent studying associated with exam performance?
  2. Descriptive statistics: Means and standard deviations for both variables
  3. Inferential statistics: r(58) = .42, p = .001
  4. Interpretation: Students who studied more tended to have higher exam scores.

APA-style write-up

I examined whether time spent studying was associated with exam performance. Students studied an average of 6.40 hours (SD = 2.15) and had an average exam score of 78.30 (SD = 9.85). Time spent studying was significantly and positively associated with exam performance, r(58) = .42, p = .001. Students who studied more tended to have higher exam scores.

Why this works

This write-up states the research question, describes both variables, reports the correlation, and interprets the direction of the relationship.

It does not say that studying caused higher exam scores. Correlation does not establish causation.

Key Takeaway

There is no single “correct” sentence structure for APA results.

What matters is that:

  • the research question or hypothesis is clear;
  • the relevant descriptive statistics are included;
  • the inferential statistics are reported correctly;
  • the result is interpreted in plain language;
  • the interpretation avoids overclaiming.
NoteA Helpful Tip

Read your results without the parentheses to check for clarity and grammar.

For example, this sentence still makes sense if we remove the parenthetical statistics:

Anastasia’s students had significantly higher grades than Bernadette’s students.

If the sentence does not make sense without the parentheses, revise the sentence structure.