A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validity of the assumptions. Cutlets.csv
Assume Null hyposthesis as Ho: μ1 = μ2 (There is no difference in diameters of cutlets between two units).
Thus Alternate hypothesis as Ha: μ1 ≠ μ2 (There is significant difference in diameters of cutlets between two units) 2 Sample 2 Tail test applicable
Anova ftest statistics
A hospital wants to determine whether there is any difference in the average Turn Around Time (TAT) of reports of the laboratories on their preferred list. They collected a random sample and recorded TAT for reports of 4 laboratories. TAT is defined as sample collected to report dispatch. Analyze the data and determine whether there is any difference in average TAT among the different laboratories at 5% significance level.
Anova ftest statistics: Analysis of varaince between more than 2 samples or columns Assume Null Hypothesis Ho as No Varaince: All samples TAT population means are same
Thus Alternate Hypothesis Ha as It has Variance: Atleast one sample TAT population mean is different
Chi2 contengency independence test
Assume Null Hypothesis as Ho: Independence of categorical variables (male-female buyer rations are similar across regions (does not vary and are not related) Thus Alternate Hypothesis as Ha: Dependence of categorical variables (male-female buyer rations are NOT similar across regions (does vary and somewhat/significantly related)
Inference: As (p-value = 0.6603) > (α = 0.05); Accept the Null Hypothesis i.e. Independence of categorical variables Thus, male-female buyer rations are similar across regions and are not related
Chi2 contengency independence test
Q4. TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5% significance level and help the manager draw appropriate inferences.
Assume Null Hypothesis as Ho: Independence of categorical variables (customer order forms defective % does not varies by centre) Thus, Alternative hypothesis as Ha Dependence of categorical variables (customer order forms defective % varies by centre)
Inference: As (p_value = 0.2771) > (α = 0.05); Accept Null Hypthesis i.e. Independence of categorical variables Thus, customer order forms defective % does not varies by centre.