Week Four Reflection
Week Four Reflection
Research is highly essential in statistics. In order to properly conduct research, we must accurately complete the steps in researching a hypothesis, compare the means of two or more groups, and calculate the correlation between two variables. In this paper, Team C will explain the steps in researching a hypothesis; illustrate a comparison between the means of two or more groups, and make a calculation of the correlation between two variables. We will also reflect on the topics in week four that we are most comfortable with and the topics we struggled with at the same time. Additionally, we will explain how the topics relate to the ...view middle of the document...
As with all other test statistics, a threshold (critical) value of F is established. This F value can be obtained from statistical tables, and is referred to as F critical or Fa. The last step is to draw a conclusion in which you have to decide the question is fact or not for example wonder bread is the softest bread on the market
Below is a picture of what can happen in a hypothesis test
| In Reality |
Decision | H0 is TRUE | H0 is FALSE |
Accept H0 | OK | Type II Error
β = probability of Type II Error |
Reject H0 | Type I Error
α = probability of Type I Error | OK |
Comparing Means of Two or More Groups
The best way to compare the means of or more groups you should state the null hypothesis. In order to show the formula and how it works is by using indiscriminate samples taken from the population. Normally to ensure that the sample is more defined the samples picked would be the higher numbers within the study. The T-test would be the best way to compare the means of two or more groups. Once all the material is collected the math part can be preformed and see what the variance between the two means of two or more groups.
Correlation between Two Groups
“Correlation is a statistical technique that can show whether and how strongly pairs of variables are related” (Surveysystem.com, 2010). The correlation between variables displays the possibility of change in one variable, leading to a sizeable change in the other variable. If there is an extensive correlation between variables, researchers can predict that the variables share a common cause, or any change in them leads to a change in the other. A good example of correlation between two variables is America’s current gas prices. As the production of oil increases, the gas prices for citizens decreases, exhibiting the correlation between the two variables. The Pearson correlation coefficient calculator is one of the most useful tools for measuring the strength and varying relationship between variables.
Comfortable and Struggled topics (Everyone)
The team feels comfortable discussing the elements of a hypothesis, knowing it is just that, a hypothesis. The mathematical formula for determining the...