Tell me which test I need

Chi Squared test

Used to determine if there is a significant association between categorical variables. It compares observed and expected frequencies to assess independence or relationships.

When to use ✅✅✅

  • Categorical Data: The Chi-Squared test is suitable for analyzing associations between categorical variables.
  • Independence Testing: It helps determine if two categorical variables are independent or related.
  • Frequency Counts: Useful for comparing observed and expected frequency counts in contingency tables.
  • Nominal or Ordinal Data: Works with nominal or ordinal-level data, but not suitable for continuous variables.
  • Large Sample Sizes: The Chi-Squared test performs well with large sample sizes, ensuring accurate results.

Fisher’s exact test

Used when dealing with small sample sizes or rare events. It assesses the association between two categorical variables without assuming normality, making it suitable for sparse data.

When to use ✅✅✅

  • Small Sample Sizes: Fisher’s exact test is suitable for analyzing associations between categorical variables when sample sizes are small.
  • Independence Testing: It helps determine if two categorical variables are independent or related, especially with sparse data.
  • Low Expected Frequencies: When expected frequency counts are below 5, Fisher’s exact test provides more accurate results than the Chi-Squared test.
  • 2×2 Contingency Tables: Specifically designed for 2×2 contingency tables.
  • Nominal or Ordinal Data: Works with nominal or ordinal-level data, but not suitable for continuous variables.

Need help? 🤝🏻

Need help selecting and applying the right statistical test? Our experts are at your service – visit digital-power.com for more info.

Statistical tests

There’s a diverse range of statistical tests, each tailored to specific situations. Make sure you use the right one! 😉

View all statistical tests

Z-test

Assesses whether the means of two populations are significantly different. It is based on the standard normal distribution and requires a known population standard deviation.

Linear regression

Used to examine the relationship between two or more variables. It helps identify and predict trends, making it valuable in various fields like economics and data analysis.

Logistic regression

Used to model binary outcomes, such as yes/no or true/false. It assesses the probability of an event occurring based on one or more predictor variables.

Z-Spearman’s Rho

Measures the strength and direction of the relationship between two ordinal variables. It assesses non-linear associations, making it valuable for ranked data.

T-test (Student)

Used to compare the means of two groups. It determines if the difference between their sample averages is significant or due to chance.

T-test (Welch)

A variation of the Student's t-test that handles unequal variances and sample sizes between two groups. It's robust and useful for analyzing data with unequal characteristics.

Chi Squared test

Used to determine if there is a significant association between categorical variables. It compares observed and expected frequencies to assess independence or relationships.

Fisher’s exact test

Used when dealing with small sample sizes or rare events. It assesses the association between two categorical variables without assuming normality, making it suitable for sparse data.

N-way ANOVA + post-hoc test

Used to analyze the effects of multiple independent variables on a dependent variable. Post-hoc tests further identify specific group differences after ANOVA analysis.

Kruskal Wallis test

Used to assess if there are significant differences among multiple groups when parametric assumptions are not met, making it suitable for non-normally distributed data.

Pearson’s R

Used to measure the strength and direction of a linear relationship between two continuous variables.

Mann Whitney U test

Used to determine if there are significant differences between two independent groups, especially when data violates normality

About us

As a fast-growing data consultancy, we help you go from data to action. Our mission? To become your data partner.

Learn more

Services

We work with you to extract the maximum value from your data. We do this with an approach that suits you, your team and your organisation.

Learn more

Careers

Whether you are a young professional or have been in the business for years: at Digital Power, you face no challenge alone.

Learn more
Cookies & Privacy