Myocardial blood flow (ml/min/g) was measured for a group of cyclists under normal oxygen levels after 5 minutes of bicycle exercise. The following is some R code and output using the "t.test" function. > t.test (normoxia, mu=3, alternative="less") One Sample t-test data: normoxia t = -2.5751, df = 9, p-value = 0.01497 alternative hypothesis: true mean is less than 3 95 percent confidence interval: -Inf 2.85968 sample estimates: mean of x 2.513 At the 0.05 significance level, identify the correct interpretation for the conclusion in the context of the setting for the hypothesis test done in the t.test output above (step 6 of a hypothesis test). Oa. There is significant evidence to conclude Myocardial blood flow tends to be greater than 3 for cyclists after 5 minutes of bicycle exercise. Ob. There is significant evidence to conclude Myocardial blood flow tends to be less than 3 for cyclists after 5 minutes of bicycle exercise. Oc. There is significant evidence to conclude Myocardial blood flow tends to be less than 0 for cyclists after 5 minutes of bicycle exercise. Od. There is significant evidence to conclude Myocardial blood flow tends to be greater than 0 for cyclists after 5 minutes of bicycle exercise.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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