Before data collection
Compute the minimum sample with Slovin's formula or Cochran's formula with finite population correction, or run an a priori power analysis for t-tests, ANOVA, correlation, and chi-square.
RESEARCH STATISTICS CALCULATORS
HOW TO USE THIS COLLECTION
Most student research follows the same path: decide how many respondents you need, confirm that the questionnaire is reliable, describe the responses, and then test the research hypotheses. SolveGrid keeps each step in a focused calculator so inputs and outputs stay easy to check.
Start with the Sample Size Calculator (Slovin, Yamane, or Cochran). After data collection, use the Cronbach's Alpha Calculator for reliability and the Likert Scale Calculator for weighted means and verbal interpretation. Use the Statistics Calculator for descriptive statistics, then the t-test, one-way ANOVA, correlation, and regression calculators to test your hypotheses.
AVAILABLE CALCULATORS
Analyse raw data, frequency tables, grouped intervals, or paired X/Y values using descriptive statistics, sample and population standard deviation, variance, quartiles, IQR, outlier checks, and regression results.
Use an inference-focused statistics workspace for t-tests, correlation, simple regression, and one-way ANOVA with visible assumptions.
Find the minimum sample size for a survey or thesis using Slovin/Yamane or Cochran's formula, with confidence level, margin of error, population size, response-rate adjustment, and a copy-ready methods sentence.
Check the internal consistency of a questionnaire scale from raw item scores, reverse-code negatively worded items, and see which items lower reliability.
Turn questionnaire frequency counts into weighted means, standard deviations, rankings, and a verbal interpretation table ready for a thesis results chapter.
Pick the right statistical test for your thesis in four questions, then see the assumptions to check and a ready-to-edit APA-style sentence for your results chapter.
Test whether two categorical variables are associated, or whether counts match expected proportions, with expected-count checks and a ready-to-use APA write-up.
Run the non-parametric alternative to the independent t-test for Likert items or skewed data, with exact p values for small samples and a ready-to-use write-up.
Check the normality assumption before a t-test or ANOVA, see the histogram and Q-Q plot, and get advice on what to do if normality is violated.
Measure agreement between two raters or coders beyond chance, with confidence intervals and weighted kappa for ordered categories.
Get the effect size for any common test in seconds, from raw summary statistics or from a reported t, F, or z value, with benchmarks and APA wording.
The non-parametric alternative to the paired t-test for pre-test/post-test and repeated measurements, with exact p values for small samples.
The non-parametric alternative to one-way ANOVA, with Bonferroni-adjusted Dunn comparisons that show which groups differ.
Assess inter-rater and test-retest reliability for numeric ratings with all six Shrout and Fleiss ICC forms and a guided model choice.
Check whether a mediator carries the effect of X on Y, with three classic z tests, the proportion mediated, and clear guidance on when bootstrapping is better.
Paste raw scores and get a complete t-test: group means and SDs, t, degrees of freedom, exact p value, confidence interval, Cohen's d, Levene's test, and a ready APA sentence.
Compare three or more group means from raw data, with a full ANOVA source table, effect sizes, assumption checks, Tukey-Kramer pairwise comparisons, and a ready APA sentence.
Measure the strength and direction of a relationship between two variables, with the right coefficient for your data, a confidence interval, a scatter plot with the regression line, and a ready APA sentence.
Run simple or multiple OLS regression from pasted columns, with SPSS-style model summary, ANOVA and coefficients tables, assumption diagnostics, a residual plot, and a ready APA sentence.
The non-parametric alternative to repeated-measures ANOVA: compare three or more related conditions on ordinal or non-normal data, with effect size and pairwise comparisons.
Test whether a proportion changed between two related measurements on the same people, with the exact test for small samples, the odds ratio, and a ready APA sentence.
Justify your sample size the way supervisors expect: choose the test, set the expected effect size, alpha, and power, and get the required N, a power curve, and a methodology sentence.
COMMON WORKFLOWS
Compute the minimum sample with Slovin's formula or Cochran's formula with finite population correction, or run an a priori power analysis for t-tests, ANOVA, correlation, and chi-square.
Check internal consistency with Cronbach's alpha, find weak or reverse-coded items, and convert response counts into weighted means and interpretations.
Calculate mean, standard deviation, quartiles, and frequency tables, then run t-tests, one-way ANOVA, and Pearson correlation with stated assumptions.
CHOOSE THE RIGHT METHOD
Record the population size, margin of error, and confidence level you used. Reviewers ask for these, and changing them after data collection weakens the study.
A composite score only makes sense if its items hang together. Report Cronbach's alpha for each subscale and reverse-code negatively worded items first.
Comparing two group means calls for a t-test, three or more groups for ANOVA, and a relationship between two numeric variables for correlation. Check the assumptions each test states.
LEARN THE FORMULA OR METHOD
COMMON QUESTIONS
Slovin's (Yamane) formula is common when the population size is known and only the margin of error is set. Cochran's formula is more defensible when you need to state the confidence level or expected proportion.
They cover the most common thesis calculations and show their working, but they do not replace a full statistics package for complex models. Check important results with your adviser or a statistician.
No. All calculations run in your browser and nothing you paste is sent to a server.
EXPLORE MORE