Question# 4: French Biscuit Manufacturer (FBM), produces two types of biscuits (i) double chocolate biscuits and (ii) tea time biscuits in two separate manufacturing units. They are interested in expanding the manufacturing units (one by one) because there is a demand in the market but facing a difficulty to decide which manufacturing unit should expand first. Company officials decided that the expansion decision was based upon monthly demand. FBM official consults you and requests to give your valuable suggestion which will be helpful for final decision. you analyzed the following normally distributed data: Monthly Sale of Biscuits Double Chocolate 8551 6314 5259 8138 8429 4807 8025 6845 6478 7513 9125 4894 9106 8775 10070 7845 6229 8459 10542 4196 Tea Time 10247 6601 7404 8919 9255 8404 6304 7803 11474 9131 13345 8118 6713 7439 10957 12098 9134 7535 10316 8125 NEED BELOW PENDING QUESTIONS Question # 5 With reference to question # 4, perform the analysis for the verification of the assumption and answer the questions given below: Write the name of statistical technique used for analysis “For the comparing the two variances, statisticianstudy ratio of two variances while when comparing the two means, study the difference of two mean.” Give the logical reason, why we study the ratio of two variances and why not the difference of two variances. Write the calculated value of test statistics Write the two tabulated value of test statistics at 0.01 level of significance. Comments about the assumption taken in question # 4, in the light of your analysis.

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Description: Question# 4: French Biscuit Manufacturer (FBM), produces two types of biscuits (i) double chocolate biscuits and (ii) tea time biscuits in two separate manufacturing units. They are interested in expanding the manufacturing units (one by one) because

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Question# 4: French Biscuit Manufacturer (FBM), produces two types of biscuits (i) double chocolate biscuits and (ii) tea time biscuits in two separate manufacturing units. They are interested in expanding the manufacturing units (one by one) because there is a demand in the market but facing a difficulty to decide which manufacturing unit should expand first. Company officials decided that the expansion decision was based upon monthly demand.

FBM official consults you and requests to give your valuable suggestion which will be helpful for final decision. you analyzed the following normally distributed data:

	Monthly Sale of Biscuits
Double Chocolate	8551	6314	5259	8138	8429	4807	8025	6845	6478	7513
9125	4894	9106	8775	10070	7845	6229	8459	10542	4196
Tea Time	10247	6601	7404	8919	9255	8404	6304	7803	11474	9131
13345	8118	6713	7439	10957	12098	9134	7535	10316	8125

NEED BELOW PENDING QUESTIONS

Question # 5 With reference to question # 4, perform the analysis for the verification of the assumption and answer the questions given below:

Write the name of statistical technique used for analysis
“For the comparing the two variances, statisticianstudy ratio of two variances while when comparing the two means, study the difference of two mean.” Give the logical reason, why we study the ratio of two variances and why not the difference of two variances.
Write the calculated value of test statistics
Write the two tabulated value of test statistics at 0.01 level of significance.
Comments about the assumption taken in question # 4, in the light of your analysis.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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