## How do you interpret kurtosis in SPSS?

Kurtosis: a measure of the “peakedness” or “flatness” of a distribution. A kurtosis value near zero indicates a shape close to normal. A negative value indicates a distribution which is more peaked than normal, and a positive kurtosis indicates a shape flatter than normal.

## What is normal kurtosis SPSS?

In SPSS, the skewness and kurtosis statistic values should be less than ± 1.0 to be considered normal.

**How do you interpret kurtosis?**

If the kurtosis is greater than 3, then the dataset has heavier tails than a normal distribution (more in the tails). If the kurtosis is less than 3, then the dataset has lighter tails than a normal distribution (less in the tails).

**What is crosstabs in SPSS?**

Cross Tabulation. A crosstabulation or a contingency table shows the relationship between two or more variables by recording the frequency of observations that have multiple characteristics. Crosstabulation tables shows us a wealth of information on the relationship between the included variables.

### What is an acceptable kurtosis value?

A standard normal distribution has kurtosis of 3 and is recognized as mesokurtic. An increased kurtosis (>3) can be visualized as a thin “bell” with a high peak whereas a decreased kurtosis corresponds to a broadening of the peak and “thickening” of the tails. Kurtosis >3 is recognized as leptokurtic and <3.

### How do you report skewness and kurtosis in SPSS?

Quick Steps

- Click on Analyze -> Descriptive Statistics -> Descriptives.
- Drag and drop the variable for which you wish to calculate skewness and kurtosis into the box on the right.
- Click on Options, and select Skewness and Kurtosis.
- Click on Continue, and then OK.
- Result will appear in the SPSS output viewer.

**What is a good kurtosis value?**

2.3.

A standard normal distribution has kurtosis of 3 and is recognized as mesokurtic. An increased kurtosis (>3) can be visualized as a thin “bell” with a high peak whereas a decreased kurtosis corresponds to a broadening of the peak and “thickening” of the tails. Kurtosis >3 is recognized as leptokurtic and <3.

**How much kurtosis is acceptable?**

between -2 and +2

The values for asymmetry and kurtosis between -2 and +2 are considered acceptable in order to prove normal univariate distribution (George & Mallery, 2010). Hair et al. (2010) and Bryne (2010) argued that data is considered to be normal if skewness is between ‐2 to +2 and kurtosis is between ‐7 to +7.

## How do you read crosstabs results?

Interpret the key results for Cross Tabulation and Chi-Square

- Step 1: Determine whether the association between the variables is statistically significant.
- Step 2: Examine the differences between expected counts and observed counts to determine which variable levels may have the most impact on association.

## How do I report cross-tabulation results in SPSS?

Using the Crosstabs Dialog Window

- Reopen the Crosstabs window (Analyze > Descriptive Statistics > Crosstabs).
- In the Row box, replace variable Rank with RankUpperUnder .
- Click Cells. In the Percentages area, check off Row, Column, and Total percentages.
- Click OK to run.

**What if kurtosis is too high?**

High kurtosis in a data set is an indicator that data has heavy tails or outliers. If there is a high kurtosis, then, we need to investigate why do we have so many outliers. It indicates a lot of things, maybe wrong data entry or other things.

**What is considered high kurtosis?**

A value of 6 or larger on the true kurtosis (or a value of 3 or more on the perverted definition of kurtosis that SPSS uses) indicates a large departure from normality. Very small values of kurtosis also indicate a deviation from normality, but it is a very benign deviation.

### How do you interpret skewness and kurtosis results?

A general guideline for skewness is that if the number is greater than +1 or lower than –1, this is an indication of a substantially skewed distribution. For kurtosis, the general guideline is that if the number is greater than +1, the distribution is too peaked.

### What value of kurtosis is acceptable?

**What is considered a high kurtosis?**

**How do I report crosstabs?**

Setup

- Go to Results > Reports.
- Click Create Report > Crosstab.
- Give your report a Title.
- Add Your Columns, also know as Banners.
- Next, add your Rows (aka Stubs).
- Finally, choose from the below crosstab options and click Add Crosstab when you are finished.
- Frequencies – These are just the counts of responses.

## What does the kurtosis value tell us?

Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. A uniform distribution would be the extreme case.

## How do you interpret skewness and kurtosis in SPSS?

For skewness, if the value is greater than + 1.0, the distribution is right skewed. If the value is less than -1.0, the distribution is left skewed. For kurtosis, if the value is greater than + 1.0, the distribution is leptokurtik. If the value is less than -1.0, the distribution is platykurtik.

**How much kurtosis is too much?**

For kurtosis, the general guideline is that if the number is greater than +1, the distribution is too peaked. Likewise, a kurtosis of less than –1 indicates a distribution that is too flat. Distributions exhibiting skewness and/or kurtosis that exceed these guidelines are considered nonnormal.” (Hair et al., 2017, p.

**How do I report cross tabulation results in SPSS?**

### What does a kurtosis of 1 mean?

### What is acceptable kurtosis value?

**What is a normal kurtosis value?**

The values for asymmetry and kurtosis between -2 and +2 are considered acceptable in order to prove normal univariate distribution (George & Mallery, 2010). Hair et al. (2010) and Bryne (2010) argued that data is considered to be normal if skewness is between ‐2 to +2 and kurtosis is between ‐7 to +7.