WPC_300__Practical_Exam_cheat_sheet.pdf.pdf

EXCEL portion

Question 1 - copy the table into the Lookup tab, then make a new table in the same

sheet ; from ascending range (use only starting value, not range): OR Highlight the table,

GO to Data tab, click sort by category ; ﬂip if necessary and THEN make the table with

the lower value , in ascending order

new column category you use → =VLOOKUP(ﬁrst value measuring,$B$2:$F$9,2,TRUE)

(2 meaning column two from the table which you are returning the value

from)

Put age cat in Rows and Count of Age in values

Question 2 - Change from count to average

Question 3 - change from average to count on values, click pe chart and add percentage

data labels

JMP portion

Question 4 - put all the variables from the answers into the Y column to see which is

correct/incorrect (Analyze→ Distribution)

Question 5 -data centrality =mean value

Question 6- distribution spread=Interquartile range= 75% quartile - 25% quartile

difference

Question 7- P value from a test? Analyze→ Distribution (put Age into Y , right click red

triangle next to Age and put “test mean” from the given question

Eg. null hypothesis is that the average population is above 50 so test mean = 50;

p value < 0.05 ; signiﬁcant so we accept the null hypothesis

Question 8 - null hypothesis is that the average population is below 50 ; p value > 0.05

so signiﬁcant and we fail to reject the null hypothesis

Question 9: Analyze → Multivariate methods → Multivariate ; put blue variables into Y

(darker red- neg sign, darker blue - pos significant , if it is a lighter color it is NOT significant)

Question 11: Simple linear regression line equation→Analyze→ Fit y by x (put Yinto Y ,

and put BMI into x) right click red triangle put “Fit Line” and get the equation

Question 12: Multiple linear regression→ Analyze→ Fit model→ Put y in Y variable, and

put the variables to measure in ‘Add; Construct model effects’ ; remove predictor

variables from Effects summary

Question 13- look at anova table; right click red triangle in Fit model → Click Regression

reports→Analysis of Variance ; look at P value and see if it less than 0.05) ; WHOLE

model test

To ﬁnd the R squared → ; right click red triangle in Fit model → Click Regression

reports→Summary of ﬁt (adjusted for multiple regression,use regular R squared for

single regression )

Question 14 -16 ﬁt model ; when looking at predictor (strong or weak) look at P value in

effects summary, Look at Parameter estimates

Question 17- Variation in the dependent variable using Least biased measure→ click

red triangle drop down → regression reports→ click Summary of Fit to add

(read R square Adj value to show the variation in the dependent variable ); (Use

Adjacent for multiple regression and regular R square for single regression)

Question 18- multicollinearity issue/concern? Click parameter estimates in Fit model

table, right click and click column→ click VIF( any value above 5 is the issue)

Question 19- what proportion of _?: Analyze→ Distribution → put ‘Y Binary’ in Y and put

Gender in “By” and click on red triangle and click: Histogram options click ‘show percent’

Question 20- logistic regression analysis : ﬁt model (put necessary values in; put Y

binary in Y and pt the variables measured in ‘construct model effects’, hit Stepwise (if

required) and click run, change to ‘Whole effects’ → click ‘Go’ → click ‘Make Model’ :

Look at Effects summary to see which is signiﬁcant or not

Overall model predictability → P value in whole model test

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