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

  1. Click on Analyze -> Descriptive Statistics -> Descriptives.
  2. Drag and drop the variable for which you wish to calculate skewness and kurtosis into the box on the right.
  3. Click on Options, and select Skewness and Kurtosis.
  4. Click on Continue, and then OK.
  5. 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

  1. Step 1: Determine whether the association between the variables is statistically significant.
  2. 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

  1. Reopen the Crosstabs window (Analyze > Descriptive Statistics > Crosstabs).
  2. In the Row box, replace variable Rank with RankUpperUnder .
  3. Click Cells. In the Percentages area, check off Row, Column, and Total percentages.
  4. 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

  1. Go to Results > Reports.
  2. Click Create Report > Crosstab.
  3. Give your report a Title.
  4. Add Your Columns, also know as Banners.
  5. Next, add your Rows (aka Stubs).
  6. Finally, choose from the below crosstab options and click Add Crosstab when you are finished.
  7. 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.