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Click on a sample for more information





Select Data Set

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Data Transformation

Rename variables and modify data types.


Variable
Rename Variable
Modify Data Type




Select Variables

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Filter Data

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Data Screening

Screen data for missing values, verify column names and data types.



                    




What do you want to do?



Comparison of one group to a hypothetical value



Comparison of two groups



Comparison of three or more groups

What do you want to do?



One Sample t Test



One Sample Variance Test



One Sample Proportion Test



Chi Square Goodness of Fit



Runs Test for Randomness

What do you want to do?



Independent Sample t Test



Paired Sample t Test



Binomial Test



Two Sample Variance Test



Two Sample Proportion Test



Chi Square Association Test



McNemar Test

What do you want to do?



One Way ANOVA



Levene Test



Cochran's Q Test

One Sample t Test

Performs t tests on the equality of means. It tests the hypothesis that a sample has a mean equal to a hypothesized value.



Variable:

Alternative:

alpha:

Mu:




                    

Independent Sample t Test

Compare the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different.



Variable 1:

Variable 2:

alpha:

Alternative:




                    

Paired Sample t Test

Tests that two samples have the same mean, assuming paired data.




Variable 1:

Variable 2:

Conf Int

Alternative:




                    

Binomial Test

Test whether the proportion of successes on a two-level categorical dependent variable significantly differs from a hypothesized value.



Variable:

Probability:



                                

N:

Success:

Probability:




                                

One Sample Variance Test

Performs tests on the equality of standard deviations (variances).It tests that the standard deviation of a sample is equal to a hypothesized value.



Variable:

Alternative:

Conf Int

Std. Deviation




                    

Two Sample Variance Test

Performs tests on the equality of standard deviations (variances).



Variable 1:

Variable 2:

Alternative:




                                

Variable:

Grouping Variable:

Alternative:




                                

One Sample Proportion Test

Compares proportion in one group to a specified population proportion.



Variable:

Probability:

Alternative:




                                

N:

Hypothesized Proportion:

Probability:

Alternative:




                                

Two Sample Proportion Test

Tests on the equality of proportions using large-sample statistics. It tests that a sample has the same proportion within two independent groups or two samples have the same proportion.



Variable 1:

Variable 2:

Alternative:




                                

Variable:

Grouping Variable:

Alternative:




                                

n1:

n2:

Alternative:

Proportion 1:

Proportion 2:




                                

One Way ANOVA

One way analysis of variance.



Variable:

Grouping Variable:



                    

Levene Test

Levene's robust test statistic for the equality of variances and the two statistics proposed by Brown and Forsythe that replace the mean in Levene's formula with alternative location estimators. The first alternative replaces the mean with the median. The second alternative replaces the mean with the 10% trimmed mean.



Variables:




                                

Variable:

Grouping Variable:



                                

Chi Square Goodness of Fit Test

Test whether the observed proportions for a categorical variable differ from hypothesized proportions



Variable:

Continuity Correction:



Expected Proportion:






                    

Chi Square Test of Association

Examine if there is a relationship between two categorical variables.



Variable 1:

Variable 2:



                    

Cochran's Q Test

Test if the proportions of 3 or more dichotomous variables are equal in the same population.



Select Variables:




                    

Runs Test for Randomness

Tests whether the observations are serially independent i.e. whether they occur in a random order, by counting how many runs there are above and below a threshold. By default, the median is used as the threshold. A small number of runs indicates positive serial correlation; a large number indicates negative serial correlation.



Variable:

Drop:

Split:

Mean:

Threshold




                    

McNemar Test

Test if the proportions of two dichotomous variables are equal in the same population.



Variable 1:

Variable 2:



                                

0


1

0

1




                                






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