Week 9 discussion

Anonymous

Question description

I need this within 24 hours. There's only 1 question to be answered.

Please notice the questions says to respond to 1 of the bulleted items & if you pick the 2nd bulleted item there are at least bullets at the end you have to answer. Please tell me whether you chose the 1st or 2nd bullet to make it easier for me. Also, I use more than 1 plagiarism checker so please make sure your work is 100% authentic. Please make sure you use at least 1 reference and cite it in your answer.

"Correlation and Regression" (Note: Please respond to one [1] of the following two [2] bulleted items):

• Debate the following statement: "Correlation means Causation." Determine whether this statement is true or false, and provide reasoning for your determination, using the Possible Relationships Between Variables listed below.

"Possible Relationships Between Variables

When the null hypothesis has been rejected for a specific a value, any of the following five possibilities can exist.

1. There is a direct cause-and-effect relationship between the variables. That is, x causes y. For example, water causes plants to grow, poison causes death, and heat causes ice to melt."

2. There is a reverse cause-and-effect relationship between the variables. That is, y causes x. For example, suppose a researcher believes excessive coffee consumption causes nervousness, but the researcher fails to consider that the reverse situation may occur. That is, it may be that an extremely nervous person craves coffee to calm his or her nerves.

3. The relationship between the variables may be caused by a third variable. For example, if a statistician correlated the number of deaths due to drowning and the number of cans of soft drink consumed daily during the summer, he or she would probably find a significant relationship. However, the soft drink is not necessarily responsible for the deaths, since both variables may be related to heat and humidity.

4. There may be a complexity of interrelationships among many variables. For example, a researcher may find a significant relationship between students’ high school grades and college grades. But there probably are many other variables involved, such as IQ, hours of study, influence of parents, motivation, age, and instructors.

5. The relationship may be coincidental. For example, a researcher may be able to find a significant relationship between the increase in the number of people who are exercising and the increase in the number of people who are committing crimes. But common sense dictates that any relationship between these two values must be due to coincidence."

• Biddle and Hamermesh (1990) built a multiple regression model to study the tradeoff between time spent in sleeping and working and to look at other factors affecting sleep:

Sleep = β0 + β1 totwrk + β2 educ + β3 age + ε

where sleep and totwrk (total work) are measured in minutes per week and educ and age are measured in years. Suppose the following equation is estimated:

Sleep = 3500 – 0.15 totwrk – 11.20 educ + 2.29 age + ε

• Discuss what would happen to someone’s sleep if they choose to work more.
• Analyze whether the factors of totwrk, educ, and age are enough factors to explain the variation in sleep. Explain which additional factors should be explored in order to explain the variation in sleep. Provide your reasoning.

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