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Unit Project Part 2

Unit Project Part 2

Criteria	Ratings	Pts
This criterion is linked to a Learning OutcomeSufficient, Appropriate, & Correct Work	35 ptsFull creditYour StatCrunch graph is complete, correct, and pertains to your unique random sample from the previous assignment. Your response to the research question is based on your work in the previous assignment; moreover it is sufficient, appropriate, and at least 90% correct.28 ptsHigh partial creditYour work is sufficient, appropriate, and at least 80% to 89% correct for the graded problem(s). 24.5 ptsPartial creditSome work is missing in the graded problem(s), or at least 70% to 79% of your work is correct.15 ptsLow partial creditFor the graded problem(s), the work is insufficient or mostly incorrect.0 ptsNo creditMuch of the work is missing or incorrect for the graded problem(s). Or, a good-faith effort to respond to the Prompt is not apparent in your initial post.	35 pts
This criterion is linked to a Learning OutcomeFeedback to Two Peers	15 ptsFull creditYou provided feedback to two different initial posts and prioritized being the first to give feedback to at least one of them. In each reply, you provided feedback specifically addressing your classmates’ work as described in the Directions section of this assignment.7.5 ptsPartial creditYou replied to one classmate and addressed their work as described in the Directions section of this assignment. 0 ptsNo creditYou did not provide feedback to your classmates as described in the Directions section of this assignment. Or, a good-faith effort to respond to the Prompt is not apparent in your initial post.	15 pts

Total Points: 50

Using Kaggle 80 cereals by Chris Crawford do this assgnment please use pictures; All analyses must be completed using Microsoft Excel, and your submitted file must include both the raw dataset and all calculations, charts, and outputs.

1. Dataset Selection

• Download a dataset containing at least 50 observations from Kaggle or any other reputable data source.
• The dataset must be included in your Excel file.

2. Descriptive Statistics

Using Excel, calculate:

Measures of Central Tendency

• Mean
• Median
• Mode

Measures of Dispersion

• Range
• Variance
• Standard deviation

Distribution Shape

• Identify whether the data is symmetric, left-skewed, right-skewed, or approximately uniform, and briefly explain your conclusion.

3. Data Visualization

Create Excel charts to represent your data:

• Bar Chart
• Box Plot

All charts must be clearly labeled and included in your Excel file.

4. Correlation and Regression Analysis

If your dataset contains more than one variable (two variables are sufficient):

• Calculate the correlation coefficient
• Perform regression analysis and find the equation of the line of best fit
• Create a scatter plot showing the relationship between the two variables

Grading Breakdown (100 points total)

• Dataset included & properly formatted: 10 points
• Descriptive statistics: 30 points
• Visualizations (charts & box plots): 20 points
• Correlation & regression analysis: 40 points

Module 27 – Linear Regression Lab (11 of 13)

Started: Apr 19 at 10:05pm

Quiz Instructions

In this activity, you will use StatCrunch and embed your results in an essay question. The essay questions are not automatically graded; your instructor will enter the points for these questions later. WARNING: you will need to enter your response to each essay question with every attempt. Your instructor will only grade the essay for your attempt with the highest total score for the automatically graded questions.

Recall the Question & Comments Tip for Success (feels like cheating but it’s not). If you have not earned 100% after your 2nd attempt on this quiz, use the discussion board below to ask for help. Give your peers or me some time to respond. Then return to the discussion board, review the responses, and submit your 3rd attempt. It’s o.k. if you submit your 3rd attempt on a quiz or checkpoint after the due date.

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Progress Check

Use this activity to assess whether you can:

• Use StatCrunch to graph a scatterplot with its least-squares regression line and to simultaneously produce the equation of the regression line along with its correlation coefficient, r.
• Identify the x with the largest absolute prediction error.
• Explain why a given data point is an outlier.

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Module 27 Discussion Board

Use the Module 27 (opens in a new tab) to ask questions or provide feedback about the problems in any Module 27 activity – including this lab.

---

Content by Cuyamaca College math faculty and licensed under the .

Learn by Doing

Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.

A list of StatCrunch directions is provided at the bottom of this text-box.

Context

The modern Olympic Games have changed dramatically since their inception in 1896. Are athletes getting better? We will use regression to investigate the change in winning times for one eventthe men’s 1,500 meter race.

Variables

Year: the year of the Olympic Games, from 1896 to 2000.
Time: the winning time for the 1,500 meter race, in seconds.

Since the winning time depends on the year, the Year since 1896 is the explanatory variable, and the Winning time is the response variable.

Data

The olympics datafile includes the winning times for the men’s 1,500-meter race since 1896. Open the olympics datafile in the Stats at Cuyamaca College group on StatCrunch ( – opens in a new tab).

Prompt

In the first two questions below, you will use StatCrunch to produce and examine the scatterplot for the olympics datafile. You will also use StatCrunch to find the regression equation and correlation coefficient.

List of StatCrunch Directions

As you work through numbers 1) and 2) below, refer back to these StatCrunch directions when you need a quick reminder.

• (do not take screenshots; please use these directions)
• (do not post attachments; please use these directions)
• (All at the same time!)

Question 13 pts

If you have not done so, open the olympics datafile in the Stats at Cuyamaca College group on StatCrunch ( – opens in a new tab).

1. Using the year since 1896 as the explanatory variable and the winning time as the response variable: graph the scatterplot with the regression line and produce the regression equation with the correlation coefficient – all at the same time ()
2. Toggle to the output page with the scatterplot and regression line. Notice that the data has a strong linear association, so it makes sense to use linear regression. (Always check the form of the scatterplot before using linear regression.)
3. Download the StatCrunch output page with your scatterplot and regression line graphed together. ()
4. Embed the .png file for your scatterplot and regression line in the text-box below. ()

p

Question 23 pts

These directions assume you have produced the Simple linear regression results in a multipage StatCrunch output window. If not please see the previous question.

• Toggle to the StatCrunch output page with the regression equation, correlation coefficient, and other statistics.
• Under the heading Simple linear regression results, copy and paste the first five lines (dependent variable, independent variable, linear equation, sample size, and R) into the text-box below. ()

p

Question 32 pts

For which of the years 1900, 1940, or 2000 is the absolute prediction error the largest?

Group of answer choices

1900

1940

2000

Question 42 pts

For the year 1896, the winning time for the men’s 1500-meter race is an outlier. In what ways is this data point an outlier? Check all that apply

Group of answer choices

an outlier with respect to Y=Time

an outlier with respect to X=Year

an outlier with respect to the form of the relationship between X and Y

Module 27 – Linear Regression Lab (11 of 13)

Started: Apr 19 at 10:05pm

Quiz Instructions

In this activity, you will use StatCrunch and embed your results in an essay question. The essay questions are not automatically graded; your instructor will enter the points for these questions later. WARNING: you will need to enter your response to each essay question with every attempt. Your instructor will only grade the essay for your attempt with the highest total score for the automatically graded questions.

Recall the Question & Comments Tip for Success (feels like cheating but it’s not). If you have not earned 100% after your 2nd attempt on this quiz, use the discussion board below to ask for help. Give your peers or me some time to respond. Then return to the discussion board, review the responses, and submit your 3rd attempt. It’s o.k. if you submit your 3rd attempt on a quiz or checkpoint after the due date.

---

Progress Check

Use this activity to assess whether you can:

• Use StatCrunch to graph a scatterplot with its least-squares regression line and to simultaneously produce the equation of the regression line along with its correlation coefficient, r.
• Identify the x with the largest absolute prediction error.
• Explain why a given data point is an outlier.

---

Module 27 Discussion Board

Use the Module 27 (opens in a new tab) to ask questions or provide feedback about the problems in any Module 27 activity – including this lab.

---

Content by Cuyamaca College math faculty and licensed under the .

Learn by Doing

Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.

A list of StatCrunch directions is provided at the bottom of this text-box.

Context

The modern Olympic Games have changed dramatically since their inception in 1896. Are athletes getting better? We will use regression to investigate the change in winning times for one eventthe men’s 1,500 meter race.

Variables

Year: the year of the Olympic Games, from 1896 to 2000.
Time: the winning time for the 1,500 meter race, in seconds.

Since the winning time depends on the year, the Year since 1896 is the explanatory variable, and the Winning time is the response variable.

Data

The olympics datafile includes the winning times for the men’s 1,500-meter race since 1896. Open the olympics datafile in the Stats at Cuyamaca College group on StatCrunch ( – opens in a new tab).

Prompt

In the first two questions below, you will use StatCrunch to produce and examine the scatterplot for the olympics datafile. You will also use StatCrunch to find the regression equation and correlation coefficient.

List of StatCrunch Directions

As you work through numbers 1) and 2) below, refer back to these StatCrunch directions when you need a quick reminder.

• (do not take screenshots; please use these directions)
• (do not post attachments; please use these directions)
• (All at the same time!)

Question 13 pts

If you have not done so, open the olympics datafile in the Stats at Cuyamaca College group on StatCrunch ( – opens in a new tab).

1. Using the year since 1896 as the explanatory variable and the winning time as the response variable: graph the scatterplot with the regression line and produce the regression equation with the correlation coefficient – all at the same time ()
2. Toggle to the output page with the scatterplot and regression line. Notice that the data has a strong linear association, so it makes sense to use linear regression. (Always check the form of the scatterplot before using linear regression.)
3. Download the StatCrunch output page with your scatterplot and regression line graphed together. ()
4. Embed the .png file for your scatterplot and regression line in the text-box below. ()

p

Question 23 pts

These directions assume you have produced the Simple linear regression results in a multipage StatCrunch output window. If not please see the previous question.

• Toggle to the StatCrunch output page with the regression equation, correlation coefficient, and other statistics.
• Under the heading Simple linear regression results, copy and paste the first five lines (dependent variable, independent variable, linear equation, sample size, and R) into the text-box below. ()

p

Question 32 pts

For which of the years 1900, 1940, or 2000 is the absolute prediction error the largest?

Group of answer choices

1900

1940

2000

Question 42 pts

For the year 1896, the winning time for the men’s 1500-meter race is an outlier. In what ways is this data point an outlier? Check all that apply

Group of answer choices

an outlier with respect to Y=Time

an outlier with respect to X=Year

an outlier with respect to the form of the relationship between X and Y

Solve the quadratic equation below and show your solution:

Find the value(s) of x.

1.Type your answers in MS word document and then send the excel file.

2.Handwritten solutions are not accepted

3.The assignment accounts for 20% of the total marks for the course.

4.Please select your data according to the ID specified in the list below in Table 1. Note that each dataset consists of 30 rows (table2). Type your selected data on the first page of your submission.

6. Make sure to choose the correct data.

7. Answer the questions using the sample data that you have generated.

8. Using MS-excel statistical functions to calculate the Descriptive Statistics measurements

Good at answering questions about statics

Question Details:

I need help completing Lab #3 (Regression) in Excel using the attached template and dataset.

IMPORTANT Read Carefully:

• Follow the assignment instructions exactly from the PDF (attached).
• Use the Excel file provided to complete all required calculations.
• Do NOT change the format of the template.
• All answers must be placed directly into the Excel file.

Requirements:

• Show all Excel formulas used (do NOT just give final answers).
• Clearly label each section (ex: Q1, Q2, etc. if applicable).
• If regression is required:
  • Use Excels Data Analysis Toolpak Regression
  • Include outputs like:
    • Coefficients
    • R-squared
    • P-values
    • Interpretation (if required in sheet)
• Make sure everything is organized, clean, and easy to follow.

Submission Format:

• Final answer must be a single Excel file (.xls or .xlsx).
• Do NOT submit explanations separately unless required in the sheet.
• Keep formatting identical to the template.

Additional Instructions (VERY IMPORTANT):
Your submission must follow this exactly:

• If any work is shown, it must be clear and organized
• Copy-paste results properly into the Excel file
• Make sure everything is correct and matches the dataset provided
• 
  

  Additional Note:

  The questions are already included inside the Excel file.Please:

  • Carefully review all tabs and sections in the spreadsheet
  • Follow the instructions written directly in the cells
  • Complete all required parts within the Excel template itself

  Do not submit answers separately everything must be done inside the provided file.

APPLICATIONIII ATTENDANCE

finish all questions