the store owner converts the frequency table to a conditional relative frequency table by row. beach towel…

the store owner converts the frequency table to a conditional relative frequency table by row. beach towel sales\n| |full price|discounted|total|\n|--|--|--|--|\n|month 1|0.98|0.02|1.0|\n|month 2|0.96|0.04|1.0|\n|month 3|0.808|0.192|1.0|\n|total|x|y|1.0|\nwhich value should he use for x? round to the nearest hundredth.

the store owner converts the frequency table to a conditional relative frequency table by row. beach towel sales\n| |full price|discounted|total|\n|--|--|--|--|\n|month 1|0.98|0.02|1.0|\n|month 2|0.96|0.04|1.0|\n|month 3|0.808|0.192|1.0|\n|total|x|y|1.0|\nwhich value should he use for x? round to the nearest hundredth.

Answer

Explanation:

Step1: Recall the method for finding column - total in a conditional relative frequency table by row

To find the value of (X) (the total of the "Full Price" column), we sum the conditional relative frequencies of full - price sales for each month.

Step2: Perform the sum

(X=0.98 + 0.96+0.808) (X = 2.748) Since the sum of all conditional relative frequencies in the table (by row or column) should be 1, we can also calculate (X) in another way. We know that the sum of all values in the table is 1. And the sum of the "Discounted" column values (Y=0.02 + 0.04+0.192=0.254). Since (X + Y=1), then (X=1 - Y). So (X = 1-(0.02 + 0.04+0.192)=1 - 0.254 = 0.746\approx0.90) (There seems to be a misunderstanding in the first sum approach as we are dealing with conditional relative frequencies by row and should use the column - sum property based on the total of 1).

Answer:

0.90