• ## Summary

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• 00:03

HERSCHEL KNAPP: Welcome to Practical Statisticsfor Nursing Using SPSS.This video shows how to process the Pearsoncorrelation and regression.You can watch the entire video or use the time sliderto navigate directly to any time point.[Correlation and Regression - Pearson, Overview]Correlation and regression analysis

• 00:24

HERSCHEL KNAPP [continued]: computes the nature of the relationship between twocontinuous variables.The relationship can be characterizedusing two parameters, direction and strength.The regression ranges between -1 and +1.The regression sign indicates the directionof the correlation.Positive correlations occur when the variables

• 00:47

HERSCHEL KNAPP [continued]: move in the same direction.When x goes up, y goes up.Or when x goes down, y goes down.Negative correlations occur when the variablesmove in opposite directions.When x goes up, y goes down.Or when x goes down, y goes up.

• 01:09

HERSCHEL KNAPP [continued]: The regression value indicates the strengthof the correlation.Values nearer to -1 or +1 are stronger than values nearerto zero.To better conceptualize the data,a scatterplot with a regression line is useful.Each point represents two scores gathered from each individual.

• 01:30

HERSCHEL KNAPP [continued]: For example, this point representstwo scores gathered on one of the patients surveyed.The patient had a length of stay of 12 daysand a depression score of 58.The regression line can be thoughtof as the average pathway through the points.The positive slope suggests that lower length of stayis associated with lower depression scores,

• 01:52

HERSCHEL KNAPP [continued]: and higher length of stay is associatedwith higher depression scores for this group of patients.To better comprehend the notion of regression,consider these three examples.Here we see a strong positive correlationbetween number of homework hours in quiz scores, wherelower homework hours are paired with lower quiz scores

• 02:13

HERSCHEL KNAPP [continued]: and higher homework hours are paired with higher quiz scores.In the second scatterplot, we seea strong negative correlation between alcohol consumptionand quiz scores, where higher alcohol consumptionis paired with lower quiz scores and lower alcohol consumptionis paired with higher quiz scores.

• 02:34

HERSCHEL KNAPP [continued]: Finally, we see a fairly weak correlationbetween baseball-throwing skills and quiz scores,where baseball-throwing skills have virtually no correlationwith quiz scores.[Correlation and Regression - Pearson, Pretest Checklist]Before running a Pearson correlation or regressionanalysis, there are three pretest criteria

• 02:54

HERSCHEL KNAPP [continued]: that need to be met.First, the data for each of the two groupsshould be normally distributed.We can check for this by observing a histogramwith a normal curve for each group.The second and third criteria, linearity and homoscedasticity,can be verified by observing the scatterplot with the regressionline.

• 03:16

HERSCHEL KNAPP [continued]: This example uses the dataset Ch 11 - Example 01 -Correlation and Regression.sav.This dataset contains three variables.Patient ID is a string variable, along with twocontinuous variables, Length of Stay

• 03:37

HERSCHEL KNAPP [continued]: and Depression scores for each patient.To check for normality, order histograms with normal curvesfor the two variables that will beinvolved in the correlation, Length of Stay and Depression.Click on Analyze, Descriptive Statistics, Frequencies.Move Length of Stay and Depression into Variables

• 04:01

HERSCHEL KNAPP [continued]: and click Charts.Select Histogram with Normal Curve.Click Continue, and uncheck Display Frequency Table.Click OK, and it'll process.The symmetrical curve on the histogram for Length of Stayshows a normal distribution.

• 04:24

HERSCHEL KNAPP [continued]: And the curve on the histogram for Depressionalso shows a normal distribution.The pretest criteria of normality is satisfied.To finalize the pretest checklist,we'll order a scatterplot with a regression line.This will also give us a more comprehensive understandingof the relationship between Length of Stay and Depression.

• 04:47

HERSCHEL KNAPP [continued]: Click on Graphs, Chart Builder.In the Choose From list, select Scatter/Dotand select the Simple Scatter option.Drag Length of Stay to the x-axis and Depressionto the y-axis.Click OK, and it'll process.

• 05:09

HERSCHEL KNAPP [continued]: To order the regression line, double-click on the scatterplotand click on the Add Fit Line at Total icon.In terms of linearity, we see that the pointslie in a fairly straight line.There are no unexpected curves or twistsin the arrangement of the points.This satisfies the linearity criteria.

• 05:32

HERSCHEL KNAPP [continued]: As for homoscedasticity, we see that the field of pointsis thicker in the middle and tapers at the ends.This satisfies the homoscedasticity criteria.[Correlation and Regression - Pearson, Test Run]To process a Pearson correlational analysis,click on Analyze, Correlate, Bivariate.

• 05:56

HERSCHEL KNAPP [continued]: Move Length of Stay and Depression to variables.Click OK, and it'll process.[Correlation and Regression - Pearson, Results]The correlation table shows a strong positive correlationof 0.789 between Length of Stay and Depression.We also see that the P value is less than 0.05,

• 06:19

HERSCHEL KNAPP [continued]: suggesting that this is a statisticallysignificant correlation.This concludes this video.

### Video Info

Series Name: Practical Statistics for Nursing Using SPSS

Episode: 13

Publisher: SAGE Publications, Inc.

Publication Year: 2016

Video Type:Tutorial

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### Segment Info

Segment Num.: 1

Persons Discussed:

Events Discussed:

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## Abstract

Chapter 13 of the nursing statistics series by Professor Herschel Knapp focuses on the Pearson correlation and regression. Knapp provides a step-by-step demonstration for a running a report in SPSS that presents the correlations in graph form.