PLEASE TYPE. 1.Come up with an example of a positive, negative, curvilinear, and

Question

PLEASE TYPE.

1.Come up with an example of a positive, negative, curvilinear, and zero relationship. Explain in your own words why we can’t use correlation to determine causality. What kind of research study would we have to use? Come up with an example explain your “correlation doesn’t equal causation” argument.

2.In your own words, describe the benefits of running a two-way ANOVA to test the different effects of 2 different factors instead of doing 2 one-way ANOVAs. Come up with a sample experiment where you would use a two-way between-subjects ANOVA. Come up with a sample experiment where you would use a two-way within-subjects ANOVA. Come up with a sample experiment where you would use a two-way mixed design ANOVA.

Explanation / Answer

Correlation are of three types:

1. In correlation, when values of one variable increase with the increase in another variable, it is supposed to be a positive correlation.

2. On the other hand, if the values of one variable decrease with the decrease in another variable, then it would be a negative correlation.

3. There might be the case when there is no change in a variable with any change in another variable. In this case, it is defined as no correlation between the two.

Causality is the area of statistics that is commonly misunderstood and misused by people in the mistaken belief that because the data shows a correlation that there is necessarily an underlying causal relationship .


The use of a controlled study is the most effective way of establishing causality between variables. In a controlled study, the sample or population is split in two, with both groups being comparable in almost every way. The two groups then receive different treatments, and the outcomes of each group are assessed.

For example, in medical research, one group may receive a placebo while the other group is given a new type of medication. If the two groups have noticeably different outcomes, the different experiences may have caused the different outcomes.

Due to ethical reasons, there are limits to the use of controlled studies; it would not be appropriate to use two comparable groups and have one of them undergo a harmful activity while the other does not. To overcome this situation, observational studies are often used to investigate correlation and causation for the population of interest. The studies can look at the groups' behaviours and outcomes and observe any changes over time.

The objective of these studies is to provide statistical information to add to the other sources of information that would be required for the process of establishing whether or not causality exists between two variables.

Let’s understand the difference between Causation and Correlation using a few examples below. Analyze the following scenarios and tell us whether there is a causal relation between the two events (X and Y). Answers are provided below.

Example 1 : X – Tier of B-school college a student gets offer for => Y – Salary after the graduation

Hypothesis – Students going to premium B-schools get higher salaries on an average. Are these B-school a cause of getting better jobs?

Answer:

Causal relation does not exist. For instance, only ambitious and intelligent people are selected from elite B-schools who further get much higher salary than the average. Hence, even if these students did not study in Tier 1 B-School, he/she still might get more than the average salaries. Hence, we have alternate reasoning issue in this case.

Hope this will be helpful to you:-)

Thanks and God Bless You :-)

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