instructor katelyn federicomy first classmate response neededoption 1 W r i t i n g

instructor katelyn federicomy first classmate response neededoption 1 W r i t i n g

Listed below is what was required with the discussion post. I will need two replys needed on 2 classmates discussions and a reply needed on what I did with my discussion post. My professor just ask me a question and need to reply to it.

Choose one of the following two prompts to respond to. In your two follow up posts, respond at least once to each prompt option. Use the discussion topic as a place to ask questions, speculate about answers, and share insights. Be sure to embed and cite your references for any supporting images.

Perform the following analysis by analyzing a possible linear relation between two variables.

Option 1:

Using the data set provided from the NOAA for Manchester, NH, select any month between January 1930 and December 1958. Use the variables “MMXT” and “MMNT” for your analysis. Begin with your chosen month and analyze the next 61 data values (i.e. 5 years and 1 month) to determine if a relationship exists between the maximum temperature (MMXT) and the minimum temperature (MMNT).

Using Excel, StatCrunch, etc. create a scatter plot for your sample. Determine the
linear regression equation and correlation coefficient. Embed this scatter plot in your
initial post.

For your responses to your classmates (two responses required): Discuss the relationships between the scatter plot, the correlation coefficient, and the linear regression equation for the sample. Comment on the similarities and differences between your correlation and linear regression equation and that of your classmates. Why are there differences since you are drawing from the same population? Did you expect the differences will be large? Why or why not?

Option 2:

Write a mathematical scenario to describe each of the scatter plots.MAT 240 6-1 Discussion Image 2

Answer prompts made by fellow students with the following information:

Discuss an alternative scenario to represent the data in the scatter plots. In this scenario, assume there is correlation but where it would be inappropriate to conclude causation.

To complete this assignment, review the Discussion Rubric document.


For the discussion boards, two options are given for you to choose from for your initial post. In your response posts, you are required to respond at least once to each option.

This week you should have a minimum of three posts in total:

  1. Your initial post to either Option One or Option Two
  2. A response to one of your peers’ responses to Option One
  3. A response to one of your peers’ responses to Option Two

In your title for your discussion post, please clearly include which option you are answering by typing “Option One: [your title]” or “Option Two: [your title].”

Please watch the following video for additional help and direction with these posts:

Fri at 5:32 PM

Hi Aimee,Thank you for your post.Great job explaining the trend of the graphs. However, for this option you needed to provide us with a scenario for the graphs. For example, what could x and y be for the positive graph and what could x and y be for the negative graph?

Instructor Katelyn Federico

my first classmate response needed

Option 1: Applications of Correlation

Betsy Gwynn posted Oct 8, 2020 9:43 PM

Hi Class,

My data points are January 1930, and February 1935. There is a positive correlation between MMXT and MMNT, and the correlation coefficient is R=0.98591703. The linear regression equation is y= 0.93453065x -90.010146

. MMNT is y and MMXT is x.

Chart, scatter chart

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image_4097678931602207736605.png(133.77 KB)

image_98828701441602207736606.png(141.5 KB)

2nd response needed

6-1 Discussion: Option 2

Tyler Elliott posted Oct 6, 2020 9:12 PM

Graph 1 shows x axis and y axis values on the increase. A good example would be Ford releasing the new 2020 Mustang Shelby GT500, where the x axis is the number of days the Shelby GT500 is being sold. The y axis is the number of Gt500’s units being sold, growing higher each day the vehicle is out. Graph 2 shows the opposite of graph 1, where you have a sudden plummet. A great example could be Tesla these past few weeks where their stocks dropped tremendously. Where the x axis is the number of days following the stock price drop and the y axis is the cost of a share in Tesla. As the days go on (x axis), the cost of a share in Tesla (y axis) drops in value, but might stay constant for a moment before falling again.