ImmersionGroup2

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Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
=__Scatterplot Questions__= ==1. Create a scatterplot using categories that you feel may influence fuel efficiency. Answer the following questions.== Answer: HorsePower and Weight - The categories will indictate that the higher the weight and horsepower, the more gas the car will use. Answer: Weight is y- axis and horsepower is the x-axis. Answer: Yes. The higher the horsepower and the heavier the car, the more gas the car will use. Answer: Positive slope. As the horsepower and the weight increases, the slope goes upward indicating the use of more gas.
 * === Identify the two categories you chose and why you thought there might be a relationship between the two BEFORE creating the scatterplot? ===
 * === Create the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order? ===
 * === Do you believe there is a relationship between the two categories? Why or why not? ===
 * === If there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories? ===

=__Regression Questions__= ==Create the linear regession equation in Excel. Include both the equation and the r 2 value on the graph. Answer the following questions.== Answer: y=8.321x + 1876 Answer: 0.545 Answer:
 * === What is your regression equation? Explain what the equation means in relation to the categories. ===
 * === What is your r 2 value? Is this a strong correlation? Why or Why not? ===
 * === Based on all the information you have, can you make any conclusions about your two categories? If so, what conclusions can you make? If not, why not? ===

=__**Analysis**__= ==Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.== Answer: Answer: >
 * === How would you determine which equation had the best relationship? ===
 * === Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why? ===

=//**Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.**//=