Refer to the ‘store preference’ variable and the ‘gender’ variable in Table 1. 2.1. Constructacross-tabulationtableoffrequencycountsbetween‘storepreference’(as the row variable) and ‘gender’ (as the column variable) of shoppers surveyed. (6) 2.2. Display the cross-tabulation as a multiple bar chart. (8) 2.3. Constructapercentagecross-tabulationtabletoshowthepercentagesplitofgender for each grocery store. (6) 2.4. How many shoppers are male and prefer to shop at Checkers? (1) 2.5. What percentage of all grocery shoppers are females who prefer Pick n Pay? (1) 2.6. What percentage of all Checkers’ shoppers are female? (1) 2.7. Ofallmaleshoppers,whatpercentageprefertoshopatSparfortheirgroceries? (1) 2.8. Is there an association between gender and store preference (i.e. does store preference differ significantly between male and female shoppers)?
Added by Sanele G.
Step 1
To do this, you need to organize the data from Table 1 (which is not provided here, so we'll assume hypothetical data for illustration purposes). Let's say we have three grocery stores (Checkers, Pick n Pay, Spar) and gender (Male, Female). Example: ``` Show more…
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