Multiple Regression in Excel for Mac

In summary, the conversation is about asking for help with performing polynomial regression on different sets of data in Excel on a Mac. The person asking has three columns with varying amounts of data and is wondering if the data needs to be equal in order to perform the regression. They later share that they have figured out the answer to their question.
  • #1
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Hi,
I was wondering if anyone familiar with excel on a mac can help me? Am i able to do polynomial regression with different x's who contain different amounts of elements? I have three columns, one contains 252 elements, another contains 53, and the last contains 12. They are all closing prices of the S&P 500 for days, weeks, and months respectively. Do they have to be equal in order to perform the regression?

Thanks!
 
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  • #2
I'm sorry you are not generating any responses at the moment. Is there any additional information you can share with us? Any new findings?
 
  • #3
I figured it out and the answer to my questions was no.
 

1. What is multiple regression in Excel for Mac?

Multiple regression in Excel for Mac is a statistical analysis tool used to examine the relationship between a dependent variable and two or more independent variables. It allows you to identify and measure the impact of each independent variable on the dependent variable.

2. How do I perform multiple regression in Excel for Mac?

To perform multiple regression in Excel for Mac, you need to first organize your data into a table with the dependent variable in one column and the independent variables in separate columns. Then, go to the Data tab, click on Data Analysis, and select Regression from the list of tools. Finally, enter the input range of your data and select the dependent and independent variables before clicking OK.

3. What is the purpose of multiple regression in Excel for Mac?

The purpose of multiple regression in Excel for Mac is to identify and understand the relationship between a dependent variable and two or more independent variables. It can help you make predictions, determine the strength of the relationship between variables, and identify which independent variables have the most impact on the dependent variable.

4. What are the limitations of multiple regression in Excel for Mac?

There are a few limitations to keep in mind when using multiple regression in Excel for Mac. First, it assumes a linear relationship between the variables, so it may not be suitable for non-linear data. Additionally, it assumes that the independent variables are not correlated with each other, which may not always be the case. Finally, it is important to remember that correlation does not necessarily imply causation, so further analysis may be needed to determine the true relationship between the variables.

5. How do I interpret the results of multiple regression in Excel for Mac?

To interpret the results of multiple regression in Excel for Mac, you should focus on the coefficient values for each independent variable. These values represent the impact of that variable on the dependent variable. A positive coefficient indicates a positive relationship, while a negative coefficient indicates a negative relationship. Additionally, the p-value can help determine if the relationship is statistically significant. The closer the p-value is to 0, the more likely the relationship is not due to chance.

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