How to Report a Simple Linear Regression in APA 7 (With Example)

A simple linear regression predicts one continuous outcome from one continuous predictor. The output has two layers, the overall model fit and the individual coefficient, and APA 7 wants both. People often report only the R-squared, or only the p value, and lose marks. This guide gives you the exact format, a worked example you can copy, and the mistakes reviewers catch.

What you need before you write a single word

An APA 7 write-up of a simple linear regression needs two layers of results.

The model fit:

1. R-squared (the proportion of variance explained).
2. The F statistic with its two degrees of freedom (regression df and residual df).
3. The p value for the model.

The coefficient for the predictor:

1. The unstandardized slope (b).
2. Its standard error (SE).
3. The standardized coefficient (beta).
4. The t value and its p value.
5. Optionally a 95% confidence interval for b, which APA 7 encourages.

The APA 7 format template

Report both layers in running text using this pattern:

A simple linear regression predicting [outcome] from [predictor] was significant, F(df1, df2) = X.XX, p = .XXX, R-squared = .XX. [Predictor] significantly predicted [outcome], b = X.XX, SE = X.XX, beta = .XX, t = X.XX, p = .XXX, 95% CI [X.XX, X.XX].

Formatting rules reviewers actually check:

• Italicize F, b, SE, t, p. R-squared and beta are reported as shown.
• No leading zero on p, R-squared, or beta (all bounded by 1). Keep the leading zero on b and the CI, which can exceed 1.
• Report both degrees of freedom for F, regression first: F(1, 98).
• Round to two decimals. If p is below .001, write p < .001.

A worked example

Suppose you predicted job performance from a conscientiousness score in 100 employees.

• Model: F(1, 98) = 22.45, p < .001, R-squared = .19
• Coefficient: b = 0.42, SE = 0.09, beta = .43, t = 4.74, p < .001, 95% CI [0.24, 0.60]

Written up in APA 7, that becomes:

A simple linear regression predicting job performance from conscientiousness was significant, F(1, 98) = 22.45, p < .001, R-squared = .19. Conscientiousness significantly predicted job performance, b = 0.42, SE = 0.09, beta = .43, t = 4.74, p < .001, 95% CI [0.24, 0.60]. For each one-point increase in conscientiousness, predicted performance rose by 0.42 points, and the model explained 19 percent of the variance in performance.

The APA 7 regression table

For anything beyond one predictor, a table is expected. Even for one predictor it reads cleanly. APA tables use horizontal rules only:

Note. N = 100. R-squared = .19, F(1, 98) = 22.45, p < .001.

Mistakes reviewers catch

• Reporting only R-squared. Give the F test for the model and the coefficient for the predictor, not just the variance explained.
• Confusing b and beta. b is the unstandardized slope in original units; beta is standardized. Report both, and remember beta drops the leading zero while b keeps it.
• A leading zero on R-squared, beta, or p. APA drops it for values bounded by 1.
• Omitting the degrees of freedom. F needs both: F(1, 98).
• Claiming causation from an observational model. "Predicts" is not "causes."
• Writing p = .000. Report p < .001.

Before you report: did the model's assumptions hold?

Simple linear regression assumes:

• A linear relationship between predictor and outcome (check a scatterplot).
• Independent residuals.
• Homoscedasticity (constant spread of residuals).
• Approximately normal residuals.

Check these with a residual plot before trusting the model. If the relationship is clearly non-linear, a straight-line model is the wrong tool.

Let KyroStat do the write-up for you

Formatting a regression, with two layers of results and the b-versus-beta rules, is where errors creep in. KyroStat fits the model, checks the residual assumptions, and hands you the finished APA 7 sentences, a publication-ready coefficient table, the plot, and the underlying Python or R code. Upload your spreadsheet, and the report is done in seconds.

Frequently asked questions

Do I report R-squared or adjusted R-squared? For a simple regression with one predictor, R-squared is fine. With several predictors, report adjusted R-squared, which penalizes adding predictors.

What is the difference between b and beta? b is the slope in the original units of the variables; beta is the standardized slope in standard-deviation units. Report both.

How do I report the degrees of freedom for the F test? Regression df first, then residual df: F(1, 98) for one predictor and 100 cases.

My p value shows as .000. What do I write? Report p < .001. A p value is never exactly zero.