ImmersionGroup1

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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:Weight, Average MPG Answer:X= Weight Y=Average MPG. Created that order to see the slope Answer:Yes, the lighter the car the better the average mpg Answer:Negative slope, as the weight increases the mpgs drop
 * === 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:The heavier the vehicle the lower the mpg. Answer:0.7042 Yes,as the weight increases the mpgs drop Answer:Yes, as the weight increases the mpgs drop
 * === 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:Linear 0.7042 Logarithmic 0.7563 Exponetial 0.7414
 * === How would you determine which equation had the best relationship? ===

Answer: >
 * === 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.**//=