Responses to mean number of hours a college student works per week | |||||||
S/N | Response_id | Age | Gender | Employment Status | Work Hours | ||
1 | 164405 | 37 | Female | Part Time | 10 | ||
2 | 164417 | 21 | Male | Part Time | 10 | ||
3 | 164419 | 19 | Female | Part Time | 35 | ||
4 | 164430 | 19 | Female | Part Time | 30 | ||
5 | 164457 | 34 | Female | Unemployed | 0 | ||
6 | 164545 | 20 | Female | Part Time | 19 | ||
7 | 164573 | 23 | Female | Full Time | 36 | ||
8 | 164609 | 18 | Female | Part Time | 13 | ||
9 | 164685 | 19 | Female | Unemployed | 0 | ||
10 | 164769 | 21 | Male | Part Time | 32 | ||
11 | 164946 | 20 | Female | Part Time | 25 | ||
12 | 165016 | 33 | Female | Unemployed | 0 | ||
13 | 165056 | 30 | Female | Unemployed | 0 | ||
14 | 165345 | 21 | Female | Unemployed | 0 | ||
15 | 165417 | 21 | Male | Part Time | 20 | ||
16 | 165440 | 21 | Female | Part Time | 15 | ||
17 | 165469 | 33 | Female | Full Time | 37.5 | ||
18 | 165473 | 19 | Female | Part Time | 30 | ||
19 | 165505 | 19 | Female | Part Time | 20 | ||
20 | 165638 | 32 | Female | Unemployed | 0 | ||
21 | 165793 | 56 | Male | Full Time | 40 | ||
22 | 165932 | 21 | Female | Unemployed | 0 | ||
23 | 166105 | 41 | Male | Full Time | 50 | ||
24 | 166209 | 19 | Female | Part Time | 30 | ||
25 | 166216 | 33 | Female | Full Time | 37.5 | ||
26 | 166389 | 38 | Female | Part Time | 20 | ||
27 | 166391 | 18 | Female | Part Time | 25 | ||
28 | 166397 | 33 | Female | Full Time | 37.5 | ||
29 | 166415 | 37 | Male | Full Time | 40 | ||
30 | 166416 | 25 | Female | Unemployed | 0 |
30 college students were surveyed and the following data was recorded for each respondent: Response_id, Age, Gender, Employment status, Work Hours. This data is listed in an Excel file that is provided. You are required to analyze this data then summarize your findings in a Report. The report will be read by people who may not be familiar with statistical terms. Therefore, it is important that your report be written in a manner that could be understood by people of varying statistical knowledge. The final report is to be submitted to your professor on the due date.
Frequency Distribution (table)
Create a frequency distribution for one of the Qualitative variables from (1) above:
Create a graph based on your frequency distribution table
Summarize your results in 1 -2 sentences.
Create a frequency distribution for the variable in excel, Age
Use 5 classes, with a class width of 10. The Upper Class limit of the first class should be 16.
Draw a histogram and Ogive based on your table. Comment on the shape of the distribution
Now add a relative frequency column and a cumulative relative frequency column.
Summarize your frequency table with 2-3 sentences.
Summary statistics about the data
Find the statistics using the formulas shown in the introduction of the report.
Finding the distribution of work hours
Put the data as shown and perform the following steps
Highlight the interval and frequency and insert the graph as shown below
From the graph, we see that 1/3 of the students work for less than 10 hours. However an about 8 students work for 30-40 hours per week.
Finding the distribution of age
Using the method described above the required things are shown
below along with the formulas.
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Review View Get Add-ins Insert Draw Page Layout Formulas Data na Ef Online Pictures 3D Models To Shapes SmartArt mmended Table Pictures otTables Icons @Screenshot bles Illustrations ? Developer Help d ? Recommended Charts a li tn till Maps PivotChart My Add-ins 3D Map Tours Line Column Win/ Loss Sparklines Add-ins Charts x fc 0 - 10 D E F G H I J K L M N O Frequency distribution for work hours We see that the min work hours is O and the max is 50 hence we make 5 classes of interval 10 as follows Next we count the number of observation that fall in each class Frequency Frequency of work hours C Work Hours - Class Inter Interval 1 Interval 1 Interval 4 Interval 3 Interval 1 Interval 2 Interval 4 Interval 2 Interval 1 Interval 4 Interval 3 Interval 1 Interval 1 Interval 1 Interval 2 Interval 2 Interval 4 Interval 3 Interval 2 Interval 1 Interval 4 Interval 1 Interval 2 Interval 3 Interval 4 Interval 5 Dju. Interval 0 - 10 11- 20 21 - 30 31 - 40 41-50 0-10 11-20 21-30 31-40 41-50
L M N O | B CDE Age We see that min age is 18 and max age is 56 hence we make 5 classes of interval 10 as follows Next we count the number of observation that fall in each class | Interval Frequency 0 - 160 17 - 26 18 27 - 36 37 - 46 47 - 56 Total Relative Frequency 0/30 0.00% 18/30 60.00% 7/30 23.33% 4/30 13.33% 1/30 3.33% Cummulative Frequency 0 0+18 18 18+7 25+4 29+1 25 30 30 Age Ogive - Age 0-16 17 - 26 27-36 3 7-46 47-56 0-16 17-26 27 - 36 37-46 47-56
Responses to mean number of hours a college student works per week S/N Response_id Age Gender...
1. Fully interpret the meaning of the coefficient on gender, x3 2. Predict the annual income for a female aged 45 with 10 years of education. How much would the predicted income have changed for a male. 3. Plot the standardized residuals against predicted income, from regression in part (a). Check for outliers and explain whether the residual plot supports the assumptions about Ɛ. What is your conclusion? Submit the graph to earn full point EDUCATION AGE...
Please help me solve this. 5K Results Age Gender Total Time Anderson SC Cornelia GA Elberton GA Williamston SC Lake Geneva WI 25.08 25.20 25.33 25.36 25.82 26.04 26.04 26.07 26.29 26.47 26.54 26.54 26.57 27.99 28.71 8:18 8:33 Anderson SC Anderson SC Anderson SC Williamston SC Elberton GA Piedmont SC Piedmont SC 12 13 8:57 15 Summerville SC Anderson SC 9:26 18 Easley SC Anderson SC Anderson SC 29.20 9:42 10:01 10:13 10:14 10:21 10:27 10:29 10:32 10:33 10:55...
a. Use t and F to test for a significant relationship between HRS1 and age. Use α = 0.05 and make sure you know what hypotheses you are using to conduct the significance tests.[3.5 points] b. Calculate and interpret the coefficient of determination R2. Based on this R2, did the estimated regression equation provide a good fit? Briefly justify your answer. Hint: If you used Excel Regression Tool to answer part c, R2was reported with your output. [2.5 points] Use the...
2) A Statistics student designs a survey for her project. Here are her survey questions: (You do not need to answer the survey questions.) How do you get to SCC? (car, bike, bus, walk, other) What is your gender? (male, female) What is your employment status? (unemployed, employed part-time, employed full- time) How many units are you taking this semester? What was your high school GPA? What is your college GPA? How many hours of sleep do you get in...
a. Using the Excel’s Regression Tool, develop the estimated regression equation to show how income (y annual income in $1000s) is related to the independent variables education(level of education attained in number of years), age ( Develop the dummy variable for the gender variable first. [ 6 points] Use the t test to test whether each of the coefficients obtained in part (a) are significant at .05 level of significance. What are your conclusions? [3 points] Use the F test...
A local retailer recently collected data on customers that frequent the store. The data are presented in the table below Items Net Sales Gender Age 1 59.25 Male 29 1 153.6 Female 33 1 33.75 Female 29 5 150.6 Female 25 2 81 Female 31 1 66.75 Female 41 2 117 Female 27 1 33.75 Female 37 2 84.78 Female 43 1 66.75 Female 33 1 44.25 Female 45 1 47.4 Female 37 9 240.6 Female 37 2 96.75 Female...
a Using the Excel’s Regression Tool, develop the estimated regression equation to show how income (y annual income in $1000s) is related to the independent variables education (level of education attained in number of years), age (Develop the dummy variable for the gender variable first. b. Use the t test to test whether each of the coefficients obtained in part (a) are significant at .05 level of significance. What are your conclusions? c. Use the F test to test...
Predict the annual income for a female aged 45 with 10 years of education. How much would the predicted income have changed for a male? [3.5 points] Plot the standardized residuals against predicted income, from regression in part (a). Check for outliers and explain whether the residual plot supports the assumptions about Ɛ. What is your conclusion? Submit the graph to earn full points. EDUCATION AGE GENDER INCOME (in $1000) 12 60 female 6.5 16 39 male 120 16 33 female...
Pls both parts for UPVOTE Using Excel create four histograms, properly labeled, depicting the data from the frequency distributions in #a and #b below. a) Using the variable Age, construct TWO frequency distributions to summarize the Ages of students born in the USA and those born outside the USA. Use 5 classes to construct your frequency distribution. For each frequency distribution, show your calculations for the class width and then list the: Lower limits and upper limits Class boundaries Class...
Problem 3. Hours of TV watched per week for a random sample of men and women from each of three age groups are collected and reported in the following table. 18-24 Age Group 25-54 55+ Male Female A) What is the most suitable statistical design to analyze this data (1 pt) B) Identify all the factor(s) and level(s) of each factors (2 pts) I summarized the data for you and obtained the following (partial ???) results. SSTOT=2412.70; SS(gender)= 353.63; SS(Age)=1,520;...