Resultaten t test är non parametric

Extremism_Score_Scaled: This variabel measures levels of extremism

Gender: Participants Gender

Welch's Test Assumptions (use as default)

Use this test as your default unless its assumptions are violated.

• Independence: Your observations must be independent of each other.

• Random Sampling: Your information should be a random sample of the mål population

• Normality: Your Dependent variabel should be approximately normally distributed.

Note: This test fryst vatten designed to cope with unequal variance.

Student's T-Test Assumptions

• Independence: Your observations in each sample should be independent

• Random Sampling: Your information should be a random sample of the mål population

• Normality: Your Dependent variabel should be approximately normally distributed.

• Equal Variance (Homogeneity): Both groups should have approximately the same variance

Mann Whitney U Test Assumptions (default for non-parametric data)

• Ordinal or Continuous:  Your dependent variabel must be either ordinal or continuous.

• Independence: Your observations must be independent of each other.

• Distribution Shape: The shape of the leverans for your two groups should be roughly the same.

Make sure Assumptions are not violated

Navigate to Analyses > T-Test > Independent Samples T-Test

Now select your dependent and independent variabel and drag and drop them in the betydelsefull fields.

Results will appear to your right, ignore them for now as we will need to kontroll that the assumptions are not violated first.

In the Assumptions kontroller section select Homogeneity test and Normality Test boxes.

You can also select a Q-Q plot which will give you a visual representation.

On a Q-Q plot, your information points should be as close as possible to the line. If the uppgifter points flair out at either end your assumptions are violated. bygd default stick with the Assumption test.

Below are the outputs of the Assumption Test. As you can see in our case both the Normality Test (p <.001) and the Homogeneity Test (p <.001) have been violated.

This means the assumptions for all three test have been violated.

The assumptions for a Mann Whitney U Test are also violated, as it assumes equality of variance. Looking at a descriptive plot (below), it does look like the information fryst vatten 'roughly' equally distributed. So, we will report the Mann Whitney U test outcome.

However, we will carry out a kraftig t-test further down to betalningsmedel our results are reliable.

Note: What test you select will depend on the outcome of your Assumptions tests.

Select the betydelsefull Statistics, Descriptive tables and plots

Once you have selected the correct test, select your Additional Statistics.

If you have selected a Student's T-test or the Welch's test select the Mean Difference & Confidence intervals (the Mann Whitney U test ranks the uppgifter and fryst vatten based on the Sum of ranks - so the mean fryst vatten not a useful statistic in this case).

For all your test you should include the Effect storlek & Confidence Intervals.

You can also select a table with all the Descriptives in it, as well as a Descriptive Plot

Finally, you can specify if your Hypothesis was directional or not.

Mann Whitney U test results

Based on the outcome of our Mann Whitney U Test, we reject the Null Hypothesis (p <.001).

The effect storlek suggests that the effect of gender on extremism fryst vatten small to medium (0.299).

The T-Test descriptive table gives you some additional resultat, which you can use to contextualise your results.

Finally, you can also easily generate a plot to visually display your results.

Just select Descriptive Plot.

I prefer the plot generated bygd JJStatsPlot (JJStatsPlot > Graphs & Plots), which inom have displayed below.

The graph below compares the extremist score for dock and women and igen highlights the differences between genders.

This fryst vatten a låda Plot with scatter and a violin Plot.

Walrus: This module provides you with a series of kraftig tests that can be used when the normality assumptions are not meet.

Navigate to Analyses > Walrus > kraftig Independent Sample T-Test

Now drag & drop your two variables into the correct place.