Using any Excel dataset, choose two quantitative variables from the dataset. For example, you might choose “age” and “weight.” Next, do the following:

  1. What is the name of the dataset you have chosen? What are the names of the two quantitative variables you are investigating?
  2. Using Excel, calculate the relationship (correlation) between these two variables. Write down your calculated r value.
  3. Given the r value you calculated in number 1 above, explain what the r value tells you about the relationship between the two variables. For example, is the relationship positive or negative? Is the relationship strong, medium, or weak?
  4. Using the two variables you have chosen, create and attach to your post a scatterplot. Does the scatterplot have a linear appearance? What does the scatterplot tell you about the relationship between your two variables?

D#6

you will learn about how to use Excel to create a linear regression equation. Please follow these steps:

  1. Choose any Excel Discussion dataset. Include the name of the dataset. From that dataset, select any two quantitative variables that you suspect will be related (such as age and height for example). What is the name of the dataset you have chosen? Which two variables did you choose?
  2. Next, using Excel, calculate the relationship (r value) between the two variables. Recall that the Excel “formula” for correlation is “=CORREL.” What is the r value for the two variables that you have chosen? Is it positive or negative? Is it strong, medium, or weak? Note that it is best to have an r value that is medium or strong. It is recommended that you try a few different variables until you find two variables with an r value between .5 and 1 (or between -.5 and -1).
  3. Next, use Excel to create a scatterplot for the two variables. You decide which variable will be dependent (y) and which will be independent (x). On the scatterplot, include the “trendline” and the “equation for the line” using Excel options. Attach your scatterplot to your post.
  4. Finally, using the equation of the line that you generated above, plug in any reasonable value for x (your chosen independent variable) and solve the equation for y (your chosen dependent variable). It is up to you to determine which of your two variables is x and which is y. What prediction do you get? Show all your work. In other words, type out the equation, plug in a value for x, and show your solution for y.

D#7

There are three types of probabilities: theoretical probability, relative frequency probability, and subjective probability. In addition, some data (such as female adult heights) are normally distributed data.

  1. From your own experience either personally or professionally, provide an example of when you have encountered or used relative probability. Start by defining relative probability. Next, describe the example and explain why it is relative probability, rather than theoretical or subjective.
  2. From your own experience either personally or professionally, provide an example of when you have encountered or used subjective probability. Start by defining subjective probability. Next, describe the example and explain why it is subjective probability, rather than relative or theoretical.
  3. Research the Internet to learn more about data that is normally distributed. When normal data are graphed with a histogram, they form a bell-shaped curve. Is normal data symmetric or skewed? What does it mean for data to be skewed left? Name a variable that you would expect to be normally distributed and explain why. For example, female height is normally distributed.

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