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Gcu mat 144 module 1 homework

15/10/2021 Client: muhammad11 Deadline: 2 Day

Major Assignment 2

This assignment uses a scoring guide. Review the scoring guide on the last tab of the spreadsheet prior to beginning the assignment to become familiar with the expectations for successful completion.

Please note that the Confidence Interval Explanation document is provided for reference and assistance with 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
You should just use information from Major Assignment 2, but if you want to retrieve fresh CPI data, here are the instrructions again. Step 1: Go to the Bureau of Labor Statistics website at the link below. 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
What is the 5 year inflation rate, that is percent increase in your CPI values? formula
If something cost $1.00 five years ago, what would it cost now? formula
Total budget from Worksheet 1 number
5 year projected budget total formula CPI Data Link
Like Topic 4 DQ 1
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 YOUR NAME: Joe Lope 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. Original Before Data Original After Data Random numbers seed
23 52 Before After 8
21 3 min = formula min = formula Recall Topic 1 DQ 2 78 67 9 1 63 52
64 35 max = formula max = formula 1. Calculate descriptive statistics for your data in the table provided in the Excel spreadsheet. Use the statistics including mean, max and standard deviations of the data to decide if it appears if there has been improvement in water quality? This requires a thorough discussion of these statistics to obtain full marks. (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.) 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 # of wells tested = formula
Richard Ketchersid: Richard Ketchersid: Use =count() # of wells tested = formula 53 41 41 5 38 26
52 38 # of wells with 0 E coli = formula
Richard Ketchersid: Richard Ketchersid: Use =Countif() # of wells with 0 E coli = formula 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 Answer Question 1 here: 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 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.) 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 Answer Question 2 here: 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 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.) 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 Nothing to answer here! 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 Questions 4-6
Before wells were dug - Millions of E.Coli per ml After wells were dug - Millions of E.Coli per ml Improvement Data: Before - After 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.
23 52 formula IMPROVEMENTS
21 3 formula min = formula All computations use column D, the "Improvement" data. 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.))
64 35 formula max = formula
54 44 formula mean= formula
72 49 formula SD = formula
50 35 formula SE = formula
52 38 formula
49 10 formula
55 32 formula Frequency Distribution
73 52 formula Low High Bins Cumulative Frequency Frequency
55 17 formula Formula/Number Formula/Number words or formula formula formula
51 37 formula Formula/Number Formula/Number words or formula formula formula 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.)
38 26 formula Formula/Number Formula/Number words or formula formula formula
28 0 formula Formula/Number Formula/Number words or formula formula formula
60 44 formula Formula/Number Formula/Number words or formula formula formula
57 40 formula Formula/Number Formula/Number words or formula formula formula
59 30 formula Formula/Number Formula/Number words or formula formula formula
60 42 formula Formula/Number Formula/Number words or formula formula formula 6. Recall that a 95% confidence interval shows a range of values that is 95% likely to contain the true value of a parameter. For example, if your 95% confidence interval for the average improvement level is (14, 18), it would mean that the true average improvement level is 95% likely to be in the range (14, 18). Now answer each of these questions: a) What would it mean for the average improvement in water quality to be 0? b) Look at the confidence interval you calculated--is the value 0 inside or outside your confidence interval? c) If the value 0 is outside your 95% confidence interval, can you conclude (with 95% confidence) that the water became cleaner? d) What if the value 0 were inside your confidence interval? Could you conclude in that case that the water became cleaner or not?
61 34 formula Formula/Number Formula/Number words or formula formula formula
57 33 formula Formula/Number Formula/Number words or formula formula formula
71 50 formula Formula/Number Formula/Number words or formula formula formula
57 40 formula (remember to create the Histogram, too).
63 38 formula
64 43 formula
63 52 formula
23 0 formula 95% Confidence Interval
21 3 formula Lower number to Higher number
64 35 formula formula to formula
54 44 formula Answer Question 6 (a):
72 49 formula
50 35 formula
52 38 formula
49 10 formula
55 32 formula
73 52 formula
55 17 formula
51 37 formula Answer Quastion 6 (b):
38 26 formula
28 0 formula Answer Question 6 (c):
60 44 formula
57 40 formula Answer Question 6 (d):
59 30 formula
60 42 formula
61 34 formula
57 33 formula
71 50 formula
57 40 formula
63 38 formula
64 43 formula
63 52 formula
23 0 formula
21 3 formula
64 35 formula
54 44 formula
72 49 formula
50 35 formula
52 38 formula
49 10 formula
55 32 formula
73 52 formula
55 17 formula
51 37 formula
38 26 formula
28 0 formula
60 44 formula
57 40 formula
59 30 formula
60 42 formula
61 34 formula
57 33 formula
71 50 formula
57 40 formula
63 38 formula
64 43 formula
63 52 formula
23 0 formula
21 3 formula
64 35 formula
54 44 formula
72 49 formula
50 35 formula
52 38 formula
49 10 formula
55 32 formula
73 52 formula
55 17 formula
51 37 formula
38 26 formula
28 0 formula
60 44 formula
57 40 formula
59 30 formula
60 42 formula
61 34 formula
57 33 formula
71 50 formula
57 40 formula
63 38 formula
64 43 formula
63 52 formula

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