Your sample would then not be representative of the population of nurses working in your hospital. You are still trying to determine the average age of nurses in your hospital, but you know that how long nurses have been in practice is related to their age, and you want to make sure that your sample reflects this population characteristic. You are aware that 20% of nurses have 1 year or less of experience and the rest have more than 1 year of experience.
You decide to use stratified random sampling to ensure that your sample is representative of the population in terms of work experience. Your results had a significant amount of sampling bias and were not representative of the population of interest; therefore, your results should not be generalized to the original population. As you take more and more samples, the resulting distribution of the average of all the dice will tend to look more and more bell-shaped.
One is that when you draw a sample in an experiment, the population variables can be distributed in any way you want, but the mean of the sample measurement will always be distributed as a normal distribution in the long run. For example, suppose you are trying to determine the average age of nurses in your hospital. In quota sampling, you select the proportions of the sample for different subgroups, just like in stratified sampling.
After deciding on the proportions of the sample, you collect subjects continuously until you have 50 day-shift subjects, 30 evening-shift subjects and 20 night-shift subjects.
I NCLUSION AND E XCLUSION C RITERIA
S AMPLE S IZE
S UMMARY
If one of the hospitals in your sample was a veterans institution with 97% male patients, would you expect the mean hemoglobin level collected only from patients at that hospital to differ from those at other hospitals. If one of the hospitals in your sample was a regional women's and children's hospital, would you expect the mean hemoglobin level collected at that hospital to be different from that of the other hospitals. Your electronic medical record database contains check-in time and room stay time for all patients seen in the past 2 years.
You would like to know the average wait time of adult patients seen in federally funded health clinics in the United States. Your analysis shows that this sample is normally distributed and representative of the population; however, the mean age in the sample is 29.4 years, and the mean age in the population is 30 years. What is this type of difference called, and what is the likely cause of the difference.
However, she did not realize that two of the five bars selected were for gay men, and another bar had a draft for the football playoff games on three of the four weekends. Questions 17-20: You want to make sure that your sample is representative of the racial admixture seen in your population of interest. Your sample is normally distributed with a mean total cholesterol of 211 and a standard deviation of 7.
In what range would you expect the total cholesterol to be for 68% of your sample. Your analysis shows that in this sample age is normally distributed and representative of the population. If a variable is measured as voting and non-voting, what level of measurement is this variable.
Your subjects must have been team captains for at least 3 months on a university-affiliated Division I sports team and be eligible to play in the upcoming season. Team captains currently on the injured or inactive list are not eligible to participate in the study. Yes, most children in this age group would be in school at this time and may not have the opportunity to be physically active until they leave school, which could affect the results.
G ENERATING THE R ESEARCH I DEA
WHAT IS MY RESEARCH IDEA?
No difference or association between variables that is any greater or less than would be expected by chance.
H YPOTHESIS T ESTING
You choose an alpha of 0.05, which means that you are willing to accept that there is a 5% chance that you will incorrectly reject the null hypothesis and report that eating a high-fiber breakfast is associated with a change in blood sugar levels at 10:00. The p-value is the probability of observing a value of a test statistic if the null hypothesis (there is no relationship, association, or difference between the variables) is true. If the actual p-value of your test statistic shows that you only have a 3% chance of making a type one error (p = 0.03), then you are within error limits that you are comfortable with (5% or less) and can you confidently reject the null hypothesis.
Now you know that if the p-value is less than alpha, you must reject the null hypothesis. However, if the p-value is greater than alpha, the chance of making a type one error is greater than the level you are comfortable with, so you should not reject the null hypothesis. In this case (p > alpha), we would fail to reject the null hypothesis and report that there is no association, association, or difference between the variables.
By subtracting the p-value from 1, you tell how certain the researcher is about rejecting the null hypothesis. If it is smaller than your alpha value, then the probability of finding this test result if the null hypothesis is true is smaller than the chance you are willing to take of being wrong about rejecting the null. This is a graphical illustration of p < alpha, which means you have statistically significant results and should reject the null hypothesis.
J.'s case, many people believed that there was enough evidence to reject the null hypothesis of innocence and find him guilty. Courts reduced the stringency of the test from establishing criminal guilt to civil liability by reducing the burden of proof necessary to reject the null hypothesis between the two tests. If your p-value is 0.07, you will reject the null hypothesis if your alpha is 0.10 (less stringent), but not if your alpha is 0.05 (more stringent).
Compare the distribution of the statistic calculated in step 3 with the distribution under the null hypothesis and report the p-value. Is the sampling distribution sufficiently different from the null distribution that we can say it is more than a random phenomenon?). A z-score, like any other test statistic you calculate, has a corresponding p-value, which is then used to decide whether to reject or reject the null hypothesis.
A PPLYING THE D ECISION R ULE
All calculated test statistics have a corresponding p-value that you need to look at to determine if there is a statistically significant difference and what conclusion to draw about the null hypothesis. If the p-value associated with the calculated test statistic is less than the alpha value chosen in the decision rule, then the null hypothesis should be rejected. The alternative hypothesis is the opposite of the null hypothesis: there is a relationship, association, or difference (which you actually think is true).
When you reject the null hypothesis, you have found statistical support for your alternative hypothesis. When you fail to reject the null hypothesis, you do not have enough statistical power to say there is a relationship or an association. For review questions 1–5, you conduct a study to determine whether there is a relationship between years worked in nursing and salary earned.
If you reject the null hypothesis, what kind of error is it if you are wrong. If the alpha for a study is set at 0.05, what should the researcher conclude about the null hypothesis. If the researchers decided to set the alpha of this pilot study to 0.10 instead of an alpha of 0.05, what would the researcher conclude about the null hypothesis (p = 0.06).
If the researcher rejects the nullity but does so by mistake, what type of error might he or she be making. Write what you would conclude about the null hypothesis given the following results at the two different levels of alpha:. If the researcher is wrong about the decision made about the null hypothesis, which studies could be a type one error at an alpha of 0.05.
If the researcher is wrong about the decision about the null hypothesis, which studies can be a type 1 error at an alpha of 0.10. The p-value is significant; therefore you conclude that there is a correlation between years performed and salary earned. There is a correlation between a positive toxicological screening for Rohypnol and signs of sexual assault.
Low-risk
S AMPLE S IZE , E FFECT S IZE , AND P OWER
SO HOW MANY SUBJECTS DO I NEED?