1.Provide a short explanation of what a SAS Studio task is.
SAS is an accounting software that allows the user to create a frequency table, pie chart, and bar graphs in a frequency distribution. The software helps in an easy computation of analytical data.
2.Generate a one-way frequency table, a pie chart, and a bar chart. Then add an additional field and generate a two-way frequency table. Download your output to a Microsoft Word document and answer this question there: What can you infer from this output?
2.1 One-way frequency table
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2.2 A pie chart
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2.3 A bar chart
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2.4 A two-way frequency table
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3.Feel free to select a data field from the same data table and generate descriptive statistics using SAS Studio's summary statistics task. Include all relevant measures, a histogram and normal density curve, inset statistics, and a box plot. Add these outputs to your Word document, then answer these questions there: Analyze your output. What do the measures tell you? Is your data skewed? Does it exhibit kurtosis? What is the interquartile range? What insights about the data you have chosen do you derive from this analysis?
The data shows a wide variation in distribution tails. it have exhibit kurtosis. The data is not skewed. A line of kurtosis leaves out the uneven distribution of data.
3.1
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Origin Frequency Percent
Cumulative
Frequency
Cumulative
Percent
Asia
158 36.92 158 36.92
Europe
123 28.74 281 65.65
USA
147 34.35 428 100.00
Analysis Variable : Invoice
Origin
N
Obs Mean Std Dev Minimum Maximum Median N
N
Miss Std Error Variance Mode Range
Asia 158 22602.18 9842.98 9875.00 79978.00 20949.50 158 0 783.0658319 96884351.34 14207.00 70103.00
Europe 123 44395.08 23080.37 15437.00 173560.00 37575.00 123 0 2081.09 532703428 19638.00 158123.00
USA 147 25949.34 10518.72 10319.00 74451.00 23217.00 147 0 867.5695843 110643517 . 64132.00
Analysis Variable : Invoice
Origin
N
Obs Sum
Lower 95%
CL for Mean
Upper 95%
CL for Mean
Coeff of
Variation Skewness Kurtosis 1st Pctl 5th Pctl 10th Pctl
Asia 158 3571144.00 21055.47 24148.88 43.5488351 2.1159219 7.9135432 10107.00 11209.00 12719.00
Europe 123 5460595.00 40275.36 48514.80 51.9885722 2.3617169 8.5886896 17427.00 19638.00 23701.00
USA 147 3814553.00 24234.72 27663.96 40.5356057 1.5375037 3.9573469 10965.00 13697.00 14607.00
Analysis Variable : Invoice
Origin
N
Obs
Lower
Quartile
Upper
Quartile 90th Pctl 95th Pctl 99th Pctl
Quartile
Range
Asia 158 16265.00 26660.00 31845.00 41100.00 56455.00 10395.00
Europe 123 31187.00 51815.00 69229.00 80939.00 119600.00 20628.00
USA 147 18881.00 30846.00 39869.00 45815.00 70546.00 11965.00
Type Frequency Percent
Cumulative
Frequency
Cumulative
Percent
Hybrid
3 0.70 3 0.70
SUV
60 14.02 63 14.72
Sedan
262 61.21 325 75.93
Sports
49 11.45 374 87.38
Truck
24 5.61 398 92.99
Wagon
30 7.01 428 100.00
Type Frequency Percent
Cumulative
Frequency
Cumulative
Percent
Hybrid
3 0.70 3 0.70
SUV
60 14.02 63 14.72
Sedan
262 61.21 325 75.93
Sports
49 11.45 374 87.38
Truck
24 5.61 398 92.99
Wagon
30 7.01 428 100.00
vivi_5488
Homework333333.docx
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