Question 1.
Let’s say you were to roll two dice 1000 times. What is the number of times you would expect the number 7 to appear?
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data_analysis.xlsx
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Question 2.
The Analysis1_DescriptiveStats worksheet contains several additives for concrete. For this question, we want you to focus specifically on the
ash additive.
You should use all of the data in the dataset, but assume that the data is a sample.
What is the standard deviation (round to the nearest 4 decimal places)?
example 12.33414 –; 12.3341
example 48.39208 –; 48.3921
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Question 3.
The Analysis1_DescriptiveStats worksheet contains several additives for concrete. For this question, we want you to focus specifically on the
air ent admix additive.
What is the mean (round to the nearest 4 decimal places)? example 48.39208 –; 48.3921
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Question 4.
The Analysis1_DescriptiveStats worksheet contains several additives for concrete.
Which additive shows the highest relative standard deviation?
Group of answer choices
cement
slag
ash
water
superplastic
air_ent_admix
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Question 5.
What can you tell us about how the Coefficient of Variation might be related to skewness? Use the data from the Analysis1_DescriptiveStats worksheet for your answer.
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Question 6.
Use the Analysis2_Correlation worksheet for this question.
Compare the most expensive additive (cement) with the overall Strength.
What patterns to you see? Does one have to invest heavily in Cement to achieve a strong concrete mixture?
In a sentence or two, what is happening with any outlier groups?
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Concrete Data
region | cement | slag | ash | water | superplastic | coarseagg | fineagg | air ent admix | strength |
midwest | 331 | 0 | 0 | 192 | 0 | 879 | 825 | 3 | 13.52 |
midwest | 154 | 174 | 185 | 228 | 7 | 845 | 612 | 28 | 24.34 |
midwest | 236.9 | 91.7 | 71.5 | 246.9 | 6 | 852.9 | 695.4 | 28 | 28.63 |
midwest | 108.3 | 162.4 | 0 | 203.5 | 0 | 938.2 | 849 | 3 | 2.33 |
midwest | 380 | 95 | 0 | 228 | 0 | 932 | 594 | 7 | 32.82 |
midwest | 184 | 86 | 190 | 213 | 6 | 923 | 623 | 28 | 22.93 |
midwest | 108.3 | 162.4 | 0 | 203.5 | 0 | 938.2 | 849 | 7 | 7.72 |
midwest | 170.3 | 155.5 | 0 | 185.7 | 0 | 1026.6 | 724.3 | 7 | 10.73 |
midwest | 155 | 0 | 143 | 193 | 9 | 877 | 868 | 28 | 9.74 |
midwest | 212 | 141.3 | 0 | 203.5 | 0 | 973.4 | 750 | 3 | 6.81 |
midwest | 102 | 153 | 0 | 192 | 0 | 887 | 942 | 7 | 7.68 |
midwest | 255 | 0 | 0 | 192 | 0 | 889.8 | 945 | 3 | 8.2 |
midwest | 380 | 95 | 0 | 228 | 0 | 932 | 594 | 28 | 36.45 |
midwest | 166.8 | 250.2 | 0 | 203.5 | 0 | 975.6 | 692.6 | 3 | 6.9 |
midwest | 284 | 15 | 141 | 179 | 5.5 | 842 | 801 | 7 | 24.13 |
midwest | 299.8 | 0 | 119.8 | 211.5 | 9.9 | 878.2 | 727.6 | 28 | 23.84 |
midwest | 144.8 | 0 | 133.6 | 180.8 | 11.1 | 979.5 | 811.5 | 28 | 13.2 |
midwest | 151.6 | 0 | 111.9 | 184.4 | 7.9 | 992 | 815.9 | 28 | 12.18 |
midwest | 152 | 0 | 112 | 184 | 8 | 992 | 816 | 28 |