Difference between pages "Histograms" and "Levene's p versus the test statistic p"

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==Histograms==
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Levene's p versus the test statistic p
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"Histograms are used to display the distribution of a single continuous variable (e.g. age, perceived stress scores)." Examining the shape of the curve will provide information about the distribution of scores of a continuous variable.  If we assume that scores of each variable measured are distributed normally, most scores will occur in the center, and taper towards the extremes. The skewness of the data is determined if the data displayed is either distributed more to right or left side of the visual.  
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When an  value is set at .05, any p that is smaller than .05 is producing a statistically significant different result, while any value greater than .05 is producing a statistically similar result.
  
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(Pallant, 2016, pg. 68)
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p≤.05   statistical difference
  
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''contributed by Joseph W. Sullivan''
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p>.05   statistical similarity
  
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==Parts of a Histogram==
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When do we want one or the other?  It depends on the question asked.  
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# The title: The title describes the information included in the histogram.
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# x-axis: The x-axis are intervals that show the scale of values which the measurements fall under.
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For example, when we are looking at two sets of data to see if they are homogenous to one another for the purpose of equal variances, we want p>.05 so there IS statistical similarity.  Therefore the Levene’s test demonstrates homogeneity (equal variance) when p>.05. (This generally results in an F≈1.)  When Levene’s is statistically similar this is a GOOD thing, because it gives us confidence that data sets have similar distributions (even though their means might be different). In other words, the curves look similar, even though their centers might be at different points on the number line.
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# y-axis: The y-axis shows the number of times that the values occurred within the intervals set by the x-axis.
 
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# The bars: The height of the bar shows the number of times that the values occurred within the interval, while the width of the bar shows the interval that is covered. For a histogram with equal bins, the width should be the same across all bars.
 
  
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''contributed by Sandra Peña''
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On a t test, you are generally trying to show a difference (although not always the case).  Therefore the p≤.05.  If p≤.05 then we know that tcrit<tstat.  If p>.05, then tcrit>tstat.
  
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==To create a histogram on SPSS, do the following:==
 
  
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1)  After entering data into SPSS, click on "Graphs", scroll down to “Legacy     
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''contributed by Frank LaBanca, EdD''
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    Dialogs", move cursor to the right and scroll down to "Histograms".
 
  
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2)  Click on the variable in the left box you want entered into the right variable box
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This is a great visual for 'significantly different and similar'.
  
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3)  Click on “display normal curve” to view the bar graph data in bell curve form
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[[File:Statistics.JPG|200px|thumb|left|alt text]]
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4)  Click "OK".
 
  
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5)  The histogram will appear PASW Output Statistic Viewer
 
  
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''contributed by John Ryan''
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''drawing by Frank LaBanca, EdD''
  
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''contributed by Jen Eraca''
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This is an informative video I found that explains Levene's Test for Equality of Variances (also known as Levene's Test for Homogeneity of Variance). 
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[https://youtu.be/4mkEZxgxMRA Levene’s Test of Homogeneity of Variance in SPSS]
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''contributed by Scott Trungadi''
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== Calculating the Levene's test for a t-test in SPSS ==
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On SPSS, go to Analyze then Compare Means. Click on Independent Samples T test. Then, choose the variable you are testing and choose the group variable. Click on definite groups and use the numbers that correlates with the two groups you are comparing. Then, you will have your Levene's p value. If the Levene's test is greater than .05, use the top row of statistics. If it is less than or equal to .05, use the bottom row of statistics.
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''contributed by Lisa Daigle''

Latest revision as of 08:37, 20 April 2022

Levene's p versus the test statistic p When an  value is set at .05, any p that is smaller than .05 is producing a statistically significant different result, while any value greater than .05 is producing a statistically similar result.

p≤.05  statistical difference

p>.05  statistical similarity

When do we want one or the other? It depends on the question asked.

For example, when we are looking at two sets of data to see if they are homogenous to one another for the purpose of equal variances, we want p>.05 so there IS statistical similarity. Therefore the Levene’s test demonstrates homogeneity (equal variance) when p>.05. (This generally results in an F≈1.) When Levene’s is statistically similar this is a GOOD thing, because it gives us confidence that data sets have similar distributions (even though their means might be different). In other words, the curves look similar, even though their centers might be at different points on the number line.

On a t test, you are generally trying to show a difference (although not always the case). Therefore the p≤.05. If p≤.05 then we know that tcrit<tstat. If p>.05, then tcrit>tstat.


contributed by Frank LaBanca, EdD

This is a great visual for 'significantly different and similar'.

alt text


contributed by John Ryan drawing by Frank LaBanca, EdD


This is an informative video I found that explains Levene's Test for Equality of Variances (also known as Levene's Test for Homogeneity of Variance). Levene’s Test of Homogeneity of Variance in SPSS

contributed by Scott Trungadi


Calculating the Levene's test for a t-test in SPSS

On SPSS, go to Analyze then Compare Means. Click on Independent Samples T test. Then, choose the variable you are testing and choose the group variable. Click on definite groups and use the numbers that correlates with the two groups you are comparing. Then, you will have your Levene's p value. If the Levene's test is greater than .05, use the top row of statistics. If it is less than or equal to .05, use the bottom row of statistics.

contributed by Lisa Daigle

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