For this assignment, I'm going to give a series of problem statements and you need to...

For this assignment, I'm going to give a series of problem statements and you need to state whether the problem would be more appropriately solved with a linear or logistic regression. You also have to give a short defense of why this is the correct regression for each one (only need a sentence or two for each).

I have a dataset of soil sample attributes (acidity, density, clay content, etc.) and whether Kentucky bluegrass successfully grew in the soil. I want to know if I will be able to grow it in my yard.
I have a dataset of highway speed limits and the amount of fatal accidents that happen on those highways annually. I'd like to know how many lives I could save if I lowered the speed limit by 5 MPH.
I've been doing testing on my website, trying to determine how much I can charge for my widgets by changing the price several times and tracking whether users buy the product. I want to know the odds someone will buy my widgets if the price is $45.
I've been tracking (and varying) my daily calorie intake and tracking weight change. I'd like to know how much weight I would expect to lose if I decreased my intake by 500 calories/day.
I have a dataset I created around my lemonade stand that I use to supplement my income. I've been tracking weather and temperature and how many glassed of lemonade I sold that day. Now I want to determine how many glasses I should be prepared to sell each day this week by looking at the weather report.

Expert Solution

1):Logistic Regression: The model should predict whether plant will be grown or not,so logistic regression will give the probability of growing plant in given situation.

2): Linear Regression: Themodel should predict number of fatal accidents with respect to speed limit and linear regression will give us a relation between speed limit and fatality

3) Linear regression: The model with llinear regression will predict number of users buying the widget with respect the price

4)Linear regression: The model should predict weight change with respect to calorie intake and so linear regression will give a relation between weight change and calorie intake

5)Linear regression: The model should predict number of lemonades sold with respect to the weather and so linear regression will give a relation between weather and number of lemonades to be prepared

(for any doubt about the answer just leave a comment)

venereology answered 9 months ago

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