Math 144 major assignment 2

Grading Sheet

Part 1

Requirements: Answer each question fully. Use Excel formulas with cell references. Answers must be recorded on the worksheet.

Possible points Points earned Comments

Five year inflation rate 10

Projection of expenses in Worksheet 1 10

Part 1 total 20 0

Part 2

Requirements: Answer each question fully. Use Excel formulas with cell references. Answers must be recorded on the worksheet.

Possible points Points earned Comments

Descriptive Statistics 16

Interpret Descriptive Statistics 14

Proportion calculations 10

Interpretation of proportions 10

Conversion of before well 5

Conversion of after well 5

Improvement level data set 5

Descriptive Statistics for improvement levels 10

Histogram 5

Standard error of the mean 5

Confidence interval 10

Discussion of the placement of 0 10

Part 2 total 105 0

Total of Worksheet 2 125 0 0%

Part 1 Inflation

Input your name here

name

Part 1 – Budget Projection: Your friends have decided to delay your dream vacation from Worksheet 1 for five years, and you need to estimate what the cost of your trip will be by then. Step 1: Go to the Bureau of Labor Statistics website at https://data.bls.gov/cgi-bin/surveymost?cu. Step 2: Check U.S. All items, 1982-84=100 Step 3: Click "Retrieve Data" Use the most recent CPI value and the CPI for the same month but five years earlier to estimate the price of your trip in five years and the five year inflation rate.

Month Year CPI

Unadjusted CPI, all items for 5 years ago number number number

Unadjusted CPI, all items for last month number number number

Inflation rate: something that cost $1.00 five years ago would cost what now? formula

What percent increase is this? formula

Total budget from Worksheet 1 number

5 year projected budget total formulahttps://data.bls.gov/cgi-bin/surveymost?cu

Part 2 Questions 1-3

Before wells were dug - Millions of E.Coli per ml After wells were dug - Millions of E.Coli per ml YOUR NAME: Joe Lope Original Before Data Original After Data Random numbers seed

23 52 Before After 8

21 3 min = formula min = formula 78 67 9 1 63 52

64 35 max = formula max = formula 19 4 17 2 4 0

54 44 mean= formula mean= formula 32 23 25 3 17 8

72 49 SD = formula SD = formula 125 110 33 4 110 95

50 35 sample size = formula/number sample size = formula/number 53 41 41 5 38 26

52 38 0 count = formula/number 0 count = formula/number 68 42 49 6 53 27

49 10 4 10 57 7 0 0

55 32 Ratio Before After 106 79 65 8 91 64

73 52 Percent Clean formula formula 38 6 73 9 23 0

55 17 36 16 81 10 21 1

51 37 Conversions 4 14 89 11 0 0

38 26 ml oz 17 5 97 12 2 0

28 0 29.5735 1 43 9 5 13 28 0

60 44 23 3 13 14 8 0

57 40 In 24 ounces 32 8 21 15 17 0

59 30 E.coli before E. coli after 49 28 29 16 34 13

60 42 formula formula 36 18 37 17 21 3

61 34 2 21 45 18 0 6

57 33 33 22 53 19 18 7

71 50 58 25 61 20 43 10

57 40 75 59 69 21 60 44

63 38 82 63 77 22 67 48

64 43 80 60 85 23 65 45

63 52 70 52 93 24 55 37

23 0 79 50 1 25 64 35

21 3 73 66 9 26 58 51

64 35 76 54 17 27 61 39

54 44 72 42 25 28 57 27

72 49 72 55 33 29 57 40

50 35 70 53 41 30 55 38

52 38 84 54 49 31 69 39

49 10 81 62 57 32 66 47

55 32 69 59 65 33 54 44

73 52 85 52 73 34 70 37

55 17 100 69 81 35 85 54

51 37 70 57 89 36 55 42

38 26 74 45 97 37 59 30

28 0 63 39 5 38 48 24

60 44 76 60 13 39 61 45

57 40 78 75 21 40 63 60

59 30 87 64 29 41 72 49

60 42 71 41 37 42 56 26

61 34 83 67 45 43 68 52

57 33 71 56 53 44 56 41

71 50 75 57 61 45 60 42

57 40 76 58 69 46 61 43

63 38 63 39 77 47 48 24

64 43 70 38 85 48 55 23

63 52 65 50 93 49 50 35

23 0 83 59 1 50 68 44

21 3 76 48 9 51 61 33

64 35 78 59 17 52 63 44

54 44 76 49 25 53 61 34

72 49 68 47 33 54 53 32

50 35 77 51 41 55 62 36

52 38 75 58 49 56 60 43

49 10 67 53 57 57 52 38

55 32 74 45 65 58 59 30

73 52 86 58 73 59 71 43

55 17 85 67 81 60 70 52

51 37 72 48 89 61 57 33

38 26 73 65 97 62 58 50

28 0 59 43 5 63 44 28

60 44 72 55 13 64 57 40

57 40 64 25 21 65 49 10

59 30 67 48 29 66 52 33

60 42 79 55 37 67 64 40

61 34 64 33 45 68 49 18

57 33 86 65 53 69 71 50

71 50 74 53 61 70 59 38

57 40 83 61 69 71 68 46

63 38 81 55 77 72 66 40

64 43 70 47 85 73 55 32

63 52 71 54 93 74 56 39

23 0 68 54 1 75 53 39

21 3 76 64 9 76 61 49

64 35 72 55 17 77 57 40

54 44 71 55 25 78 56 40

72 49 86 77 33 79 71 62

50 35 86 62 41 80 71 47

52 38 88 67 49 81 73 52

49 10 78 59 57 82 63 44

55 32 73 45 65 83 58 30

73 52 84 57 73 84 69 42

55 17 78 53 81 85 63 38

51 37 77 57 89 86 62 42

38 26 88 68 97 87 73 53

28 0 83 61 5 88 68 46

60 44 70 32 13 89 55 17

57 40 65 48 21 90 50 33

59 30 74 52 29 91 59 37

60 42 73 53 37 92 58 38

61 34 79 58 45 93 64 43

57 33 87 59 53 94 72 44

71 50 79 57 61 95 64 42

57 40 77 55 69 96 62 40

63 38 66 52 77 97 51 37

64 43 73 58 85 98 58 43

63 52 85 63 93 99 70 48

77 55 1 100 62 40

Part 2 – Data Analysis: Enter your name in cell F1 to generate data. You have just completed a mission to Sierra Leone. The goal of the mission was to improve the quality of water in 100 wells in a certain region. You collected data on the E. coli count from each well before and after your mission. You need to write a report on the success of the mission and for that you need to perform some statistical analysis on the data. You will be looking at the data from different perspectives to determine if the water quality has improve. 1. Calculate descriptive statistics for your data in the table provided in the Excel spreadsheet. Use the means and standard deviations of the data to decide if it appears that there has been improvement in water quality? (Fill in the before (F3:F8) and after (H3:H8) tables to the left for the descriptive statistics. The data has been named before and after for your convenience in creating formulas.) Answer here: 2. The water quality is “good” if the count of E coli is 0; otherwise, the water quality is still bad. Calculate the proportion of wells with “good” water to wells whose water is not good. From this measure does it appear that the quality of water improved? Explain and use the proportions that you calculated. (In G11 and H11 calculate the percent Clean for before and after.) Answer here: 3. Look at well #1 (B2 and C2) in your data. If you drank 24oz of water how many E.coli would you ingest if you drank from the well before the mission? After the mission? (In E19 and G19 calculate how many E.coli would you ingest if you drank 24 oz. of water from Well 1 before the mission and after the mission.)

Part 2 Questions 4-6

Before wells were dug - Millions of E.Coli per ml After wells were dug - Millions of E.Coli per ml Improvement Level: Before - After

23 52 IMPROVEMENTS

21 3 min = formula

64 35 max = formula

54 44 mean= formula

72 49 SD = formula

50 35 SE = formula

52 38

49 10

55 32 Frequency Distribution

73 52 Low High Bins Cumulative Frequency Frequency

55 17 Formula/Number Formula/Number words or formula Formula Formula

51 37 Formula/Number Formula/Number words or formula Formula Formula

38 26 Formula/Number Formula/Number words or formula Formula Formula

28 0 Formula/Number Formula/Number words or formula Formula Formula

60 44 Formula/Number Formula/Number words or formula Formula Formula

57 40 Formula/Number Formula/Number words or formula Formula Formula

59 30 Formula/Number Formula/Number words or formula Formula Formula

60 42 Formula/Number Formula/Number words or formula Formula Formula

61 34 Formula/Number Formula/Number words or formula Formula Formula

57 33 Formula/Number Formula/Number words or formula Formula Formula

71 50 Formula/Number Formula/Number words or formula Formula Formula

57 40 (remember to create the Histogram, too).

63 38

64 43

63 52

23 0 95% Confidence Interval

21 3 Lower number to Higher number

64 35 formula to formula

54 44

72 49

50 35

52 38

49 10

55 32

73 52

55 17

51 37

38 26

28 0

60 44

57 40

59 30

60 42

61 34

57 33

71 50

57 40

63 38

64 43

63 52

23 0

21 3

64 35

54 44

72 49

50 35

52 38

49 10

55 32

73 52

55 17

51 37

38 26

28 0

60 44

57 40

59 30

60 42

61 34

57 33

71 50

57 40

63 38

64 43

63 52

23 0

21 3

64 35

54 44

72 49

50 35

52 38

49 10

55 32

73 52

55 17

51 37

38 26

28 0

60 44

57 40

59 30

60 42

61 34

57 33

71 50

57 40

63 38

64 43

63 52

Part 2 – Data Analysis: You have just completed a mission to Sierra Leone. The goal of the mission was to improve the quality of water in 100 wells in a certain region. You collected data on the E. coli count from each well before (Q1) after your mission (Q2). You need to write a report on the success of the mission and for that you need to perform some statistical analysis on the data. You will be looking at the data from different perspectives to determine if the water quality has improved. 4. Since you collected water from the same source twice it makes sense to analyze the amount by which each well’s water quality improved. Calculate a data set that would measure the improvement level of each well, and the descriptive statistics for that data set, including both the standard deviation and standard error (SE) for the data set. (see section 3.5 of the textbook). Make a frequency distribution and histogram for your data. (Calculate the improvement in the water quality of each well in column D. (Difference in Level of e. Coli.) Then, fill out the two tables to the left and make a histogram of the improvement levels. (NOTE: The Standard deviation of this data set is not the same as the standard error. Use the formulas from section 3.5 of the text to calculate the standard error of the means.)) 5. You have calculated one sample of 100 wells and their improvement levels. If you could take all possible samples of 100 wells, the distribution of all of those sample means would be a normal distribution. (see section 3.5). Find the 95% confidence interval of that distribution, using your sample mean as the population mean and the standard error of your sample as the population standard deviation. (Calculate the 95% confidence interval of the sampling distribution in cells F24 and H24.) 6. Suppose that 0 was inside of the 95% confidence interval. From that measure, could you conclude that the water became cleaner? Why or why not? Suppose that 0 was outside the 95% confidence interval. From that measure, could you conclude that the water became cleaner? Why or why not? Answer here:

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