# gathered data

NEWS has gathered data over the last 52 weeks. Two of the data items that have been gathered are Profit and the Number of Defective Items. | |||||||||||||||

Question 1: Using the data given below, complete Task 1 and provide a very brief, general description of whether or not a relationship exists | |||||||||||||||

between Profit and the Number of Defective Items. | |||||||||||||||

ANSWER: | |||||||||||||||

A downward trend is observed between profit and number of defectives. The points are close to each other implying there is a strong neagtive linear relationship between profit and number of defectives. | |||||||||||||||

Question 2: Using the data given below, complete Task 2 and provide a statistical description of whether or not a relationship appears to exist | |||||||||||||||

between Profit and the Number of Defective Items. | |||||||||||||||

ANSWER: | |||||||||||||||

Since the value is close to -1, I observe there is a strong negative linear relaitonship between Number of Defective Items and profits. | |||||||||||||||

by taking the sqrt of R^2 there is a negative linear relationship between profit and number of defects. | |||||||||||||||

Week | Profit (thousands) | Number of Defective Items | |||||||||||||

1 | $ 35.00 | 974 | |||||||||||||

2 | $ 490.00 | 693 | Task 1: Create a Scatterplot | ||||||||||||

3 | $ 777.00 | 248 | Step 1. Highlight the two columns of data (Profit, Defective Units) | ||||||||||||

4 | $ 922.00 | 277 | Step 2. Click the Quick Analysis icon on the bottom right | ||||||||||||

5 | $ 519.00 | 509 | Step 3. Select Charts and Scatter | ||||||||||||

6 | $ 520.00 | 635 | |||||||||||||

7 | $ 899.00 | 200 | Place the Chart below this row | ||||||||||||

8 | $ 391.00 | 743 | |||||||||||||

9 | $ 577.00 | 563 | |||||||||||||

10 | $ 419.00 | 715 | |||||||||||||

11 | $ 667.00 | 397 | |||||||||||||

12 | $ 399.00 | 720 | |||||||||||||

13 | $ 540.00 | 659 | |||||||||||||

14 | $ 954.00 | 123 | |||||||||||||

15 | $ 1,078.00 | 8 | |||||||||||||

16 | $ 563.00 | 444 | |||||||||||||

17 | $ 619.00 | 464 | |||||||||||||

18 | $ 625.00 | 483 | |||||||||||||

19 | $ 351.00 | 715 | |||||||||||||

20 | $ 674.00 | 444 | |||||||||||||

21 | $ 547.00 | 639 | Task 2: Correlation and Regression Fitted Line | ||||||||||||

22 | $ 578.00 | 503 | Step 1. Place your mouse over any point within your scatterplot above and right click. Then select Add Trendline. | ||||||||||||

23 | $ 609.00 | 565 | Step 2. Select Linear, then scroll down and Display Equation and R squared Value on Chart | ||||||||||||

24 | $ 228.00 | 785 | Step 3. Place the values in a visible area of the chart so that they are legible and not covered by any of the data | ||||||||||||

25 | $ 871.00 | 286 | |||||||||||||

26 | $ 188.00 | 842 | Determine the Correlation Coefficient (R), using the CORREL function and highlighting each column (Profit, Defective). | ||||||||||||

27 | $ 632.00 | 480 | CORRELATION COEFFICIENT = | (0.977) | |||||||||||

28 | $ 442.00 | 721 | |||||||||||||

29 | $ 442.00 | 571 | Check the Correlation Coefficient (R) by taking the square root (SQRT) of the R squared value in the chart above. | ||||||||||||

30 | $ 1,114.00 | 25 | Determine the sign (+ or -) of R based on the direction of the regression line. | ||||||||||||

31 | $ 864.00 | 272 | |||||||||||||

32 | $ 825.00 | 241 | CORRELATION COEFFICIENT = | 0.977 | Strong negative association (r= -0.9) generally observed between the profit amount and the number of defective items. | ||||||||||

33 | $ 750.00 | 252 | |||||||||||||

34 | $ 615.00 | 500 | |||||||||||||

35 | $ 445.00 | 674 | |||||||||||||

36 | $ 282.00 | 732 | |||||||||||||

37 | $ 409.00 | 701 | |||||||||||||

38 | $ 637.00 | 401 | |||||||||||||

39 | $ 646.00 | 536 | |||||||||||||

40 | $ 999.00 | 156 | |||||||||||||

41 | $ 232.00 | 824 | |||||||||||||

42 | $ 152.00 | 964 | |||||||||||||

43 | $ 874.00 | 212 | |||||||||||||

44 | $ 981.00 | 218 | |||||||||||||

45 | $ 289.00 | 747 | |||||||||||||

46 | $ 771.00 | 356 | |||||||||||||

47 | $ 806.00 | 303 | |||||||||||||

48 | $ 921.00 | 113 | |||||||||||||

49 | $ 150.00 | 883 | |||||||||||||

50 | $ 113.00 | 910 | |||||||||||||

51 | $ 1,084.00 | 85 | |||||||||||||

52 | $ 350.00 | 745 | |||||||||||||