# Math 144 Major Assignment 2

Part 1

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

Possible points
Points earned

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

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

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
formula

https://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
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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