Please show excel formulas for the below calculations

Question 21: Chi-square Goodness of Fit

DATA:

	Territory
	A	B	C	D	E
Sales Volume	110	140	90	106	100

A sales region has been divided into five territories, each of which was believed to have equal sales potential. The actual Sales Volume for several sampled days is logged in DATA. At = 0.05, do the territories have equal Sales Volume?

Question 21 options:

- None of the answers match my calculation.

- H0: Territories have equal Sales Volume is not rejected with pvalue 0.334. The counts are consistent with the model of equal proportions.

- H0: Territories have equal Sales Volume is not rejected with pvalue 0.074. The counts are consistent with the model of equal proportions.

- H0: Territories have equal Sales Volume is rejected with pvalue 0.041. The counts are not consistent with the model of equal proportions. Territories have unequal Sales Volume.

- H0: Territories have equal Sales Volume is rejected with pvalue 0.012. The counts are not consistent with the model of equal proportions. Territories have unequal Sales Volume.

Hint for Question 21

"do the territories have equal Sales Volume" translates to test H0: Sales Volumes are equal.

The chi square test will determine if the observed volumes differ significantly from the expected volumes under H0. Assuming H0 is true, the expected volumes are equal. If H0 is true, the total of the sales volume is distributed equally. How was this computed?

Question 22 Correlation- Qualitative Assessment

DATA:

variable1	variable2
5.92418	16.01040
-2.15342	6.90096
-5.68710	3.20965
-2.35173	8.11837
9.13267	20.86393
8.84593	17.88436
0.60205	11.33976
4.30225	13.72104
-9.69073	0.22652
-6.81619	2.88607
7.00841	14.48358
4.48845	15.56499
3.06470	11.36857
-9.46731	1.14076
1.54090	12.95229
-4.20144	5.79307
6.11798	15.91570
9.94412	16.96745
1.32124	10.86254
-7.69106	1.10462
5.89874	15.93450
-0.72913	10.47150
8.39173	17.99690
-9.46846	0.72233

Scatter plots are used to discover relationships between variables. Using the corresponding measurements of variable1 and variable2 inDATA, plot variable1 vs. variable2 and describe the correlation between variable1 and variable2.

Question 22 options:

	-	The strength of the relationship is moderate, linear, and positive.
	-	There is no relationship, or the strength of the relationship is very weak
	-	The relationship is linear, positive, and strong.
	-	The strength of the relationship is strong, but it is not linear.
	-	The strength of the relationship is moderate, linear, and negative.
	-	None of the answers accurately characterize the data.
	-	The relationship is linear, negative, and strong.
	Hide hint for Question 22
	Plot the data. Is there one cloud of points or more than one (bimodal)? Does the point "cloud" have a discernible shape (linear or curved)? Are the points widely or narrowly scattered relative to the overall pattern? Compute the correlation R. Value of correlation R: Strength of linear relationship -1.0 to -0.5, or +1.0 to +0.5: Strong -0.5 to -0.3, or +0.5 to +0.3: Moderate -0.3 to -0.1, or +0.3 to +0.1: Weak -0.1 to +0.1: None or very weak A correlation of 0.8 is considered by some as strong for business applications. A correlation of 0.6 is considered by some as good for social science applications. Question 23- Quantitative Evaluation
variable1	variable2
-1.60263	6.66630
5.13511	22.39796
6.36533	48.04439
5.62218	33.73949
-2.19935	13.13368
6.44037	34.07411
7.53576	57.43268
6.84911	46.18391
-0.96507	2.31758
-7.97987	66.45126
7.71148	60.12220
8.00414	69.34776
-1.84249	-8.58487
-6.64529	35.44469
3.52281	15.81326
6.12823	42.51683
-8.02429	63.53322
1.93739	10.39306
1.60250	-1.67370
9.59542	92.44574
0.97873	-2.22144
7.61991	66.59948
6.35683	35.62167
4.60624	15.37388

Correlation is used to discover relationships between variables. Evaluate the correlation between the variables inDATA. What is the correlation (round to 3 decimal digits)?

Question 23 options:

-	0.984
-	-0.991
-	0.310
-	-0.008
-	None of the answers match my calculation.