William (peer 1)
Within this week’s discussion, I would like to give two examples of a psychological study within a T-test.
T-test # 1: This would be a study of a fitness practitioner that claims that there are more men come into a fitness center to work out during a month than women. The null hypothesis (X + 1) symbolizes the men and it would actually be the mean of the men that come into the fitness center to work out during a month. The alternative hypothesis would also not be the (x + 1), this would also show that this hypothesis isn’t accurate. In order to obtain accurate results/data would be by calculating the registered number of men as well as women that come into the fitness center to work out during a one month span. I would suggest that the number would possibly be about 25. So, with these different sample data results of collecting the proper number of men coming into the fitness center if they’re more than the women that come into the fitness center to work out within one month. Since we know what the standard deviation within this study sample; a T-test would be appropriate because there are less than the number of 30.
T-test # 2: This study would suggest that a pit bull dog would get sick and have to go visit the animal clinic or hospital once a month. The null hypothesis that represents the pit bull dog would be 1 and the mean would be once a month that a pit bull dog have to visit the animal clinic or hospital. The alternative hypothesis could actually be another number instead of 1, and this shows that the hypothesis wouldn’t be accurate. We can accurately collect the data results to see if a pit bull dog would actually come into an animal clinic or hospital within a month’s span. We could presume that the amount of pit bull dogs that come into an animal clinic or hospital would probably be about 10 within a 12 month span but not one pit bull dog each month. Since we are able to have 10 data collections for accurate results pertaining towards the right number of pit bull dogs that go and visit an animal clinic or hospital within a month. It would be appropriate to conduct a T-test even though the number is less than 30 because we also know what the standard deviation.
Edited by William Burton on Nov 24 at 11:53pm
Stephanie (peer 2)
Paired T-test: A doctor studies a group of ten anxiety-stricken patients before and after prescribing and administering anxiety medication. A T-test is appropriate for this study because it is used to determine if there is a significant difference between the means of two groups.
Population 1: Group of patients before treatment.
Population 2: Group of patients after treatment.
Independent Variable: Following prescription orders (measured in doses)
Dependent Variable: Level of decreased anxiety (measured 0-100%); Ordinal scale measurement
Unpaired T-test: A researcher measures the heart rate of individuals who say they never drink energy drinks. The same researcher also measures the heart rate of individuals who just drank an energy drink. A T-test is appropriate for this study because heart rates can be compared easily, although more than likely, data will be skewed.
Population 1: Heart rate of non-energy drink consumers
Population 2: Heart rate of energy drink consumers
Independent Variable: Energy drink consumed or not
Dependent Variable: Heart rate (measured in Beats Per Minute); Ordinal scale measurement
My work
Single-Sample T-Test:
My first study would be based on a mother claiming that the average child gets sick once a month. The null hypothesis would be 1, which is the mean amount of time that a child is sick. The alternative hypothesis would be anything but 1, which is showing that the hypothesis is not correct. This study would be conducted by gathering a sample of children, maybe 20, and collect data on how often they get sick over a month. There would be 20 different collections of data pertaining to sicknesses over a month. A t-test is appropriate because the sample is less than 30 and we know the standard deviation of the sample.
Independent Sample T-Test:
My second study would be based on the question of whether female babies get sick more often than male babies. There are 100 female babies and 100 male babies. I would split it up into groups of 10 each. I would find the mean and standard deviations of the number of times each baby got sick over the course of a year. The null hypothesis would end up being the 2 equal population means. The independent sample t-test is appropriate because there are 2 populations to compare.
My instructor question
I don’t understand where the “1” comes from in your first null hypothesis… can you explain a bit more?
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