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Select the type of data that you would like to upload

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When your data is uploaded to the Intellectus Statistics™ application you should confirm your levels of measurement are as follows for each analysis:

Pearson Correlation: All variables are scale level of measurement

One way ANOVA: Independent variable is nominal level of measurement; dependent variable is scale

Independent samples t-test: Independent variable is a dichotomous nominal; dependent variable is scale

Dependent samples t-test:  both variables are scale

Chi-square: x variable (factor) is nominal; Y variable (factor) is nominal

Linear regression: Dependent variable is scale; predictor(s) scale, ordinal, or nominal

Mediation: Continuous or dichotomous categorical variable

Moderation: Continuous or dichotomous categorical variable

Reliability: All variables should be the same level of measurement with themselves (e.g., only ordinal variables used together)

Logistic regression: Independent variables are nominal or scale; dependent variable is dichotomous

Wilcoxon signed rank: Both variables are ordinal (or scale)

Mann Whitney U: Independent variable is dichotomous; dependent variable is ordinal (or scale)

Kruskal Wallis: Independent variable is nominal with three or more levels; dependent variable is ordinal (or scale)

Friedman Test: All variables are ordinal (or scale)

Repeated measures ANOVA: All variables are scale

One-within One between ANOVA: Independent variable is nominal; dependent variables are scale

ANCOVA: Independent variable is nominal; covariates are scale; dependent variable is scale

Two-Between ANOVA: Dependent variable is scale; independent variables are nominal

Nominal: In this level of measurement, alphanumeric characters or names are used to categorize the data. For example, if gender is your variable, the responses will be male or female.

Ordinal: Ordinal level variables have a meaningful order to them such as rank. For example there is an order to “drink size” (small, medium, large, extra large), however there is not a consistent interval (volume, distance, time, etc.) among categories.

Scale: Numeric variables that have equal intervals between each value, for example age. For example, the amount of time between a 1 year old and 2 year old is the same amount of time as a 51 and 52 year old.