Researchers want to know if coffee improves athletic endurance. They randomly assign 50 people to drink a cup of coffee, and 50 people to not drink coffee. Then all participants are asked to walk on a treadmill until they get tired. Researchers hypothesize that coffee drinkers will show more athletic endurance and walk on the treadmill for longer than non-coffee drinkers. What statistical test should researchers use to test their hypothesis? O At-test A chi-square A Pearson correlation An ANOVA

What is the null hypothesis of a test for correlation? There is correlation in the population. There is positive correlation in the population. There is no correlation in the population. There is negative correlation in the population.

ab! ourses The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 13.6 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 13.6 cm, what is the single value that is the best predicted height for that person? "se Hom E Click the icon to view the technology output. abus The single value that is the best predicted height is cm. endar (Round to the nearest whole number as needed.) entation ktbook a-F on unouncem ssignment: cudy Plan radebook Hydrogen Report.pdf Enter your answer in the answer box. Screen Shot 20-11...9.53 P 5,981 10 tv MacBook Pro (5

10.In a study we reject Ho Which of the following statements are incorrect and why? (a) "Now we know that H, is false." (b) "We have proof that our sample mean represents a particular p." (c) "We have proof that the independent variable causes scores to change as predicted." (d) "It is not pos- sible that the difference between X and u is due to sampling error." (e) "We have evidence that the predicted relationship does

In running a Pearson correlation, you notice that there are a few outliers. Please describe the next course of action, if any, for the dataset and explain your reasoning.

An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height.  To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured  by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated.   Identify the correct null hypothesis   A. H0: There is no relationship between leg power and jump height B. H0: There is a relationship between leg power and jump height C. HA: There is a relationship between leg power and jump height D. HA: There is no relationship between leg power and jump height

An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height.  To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured  by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated. What does this type of correlation indicate about how leg strength and jump height change together?    A. Both leg strength and jump height increase and decrease together B. There is no relationship between leg strength and jump height C. As leg strength increases, jump height decreases D. As jump height increases, leg strength decreases

Choose the appropriate statistical test. When computing, be sure to round each answer as indicated. A dentist wonders if depression affects ratings of tooth pain. In the general population, using a scale of 1-10 with higher values indicating more pain, the average pain rating for patients with toothaches is 6.8. A sample of 30 patients that show high levels of depression have an average pain rating of 7.1 (variance 0.8). What should the dentist determine? 1. Calculate the estimated standard error. (round to 3 decimals). [st.error] 2. What is thet-obtained? (round to 3 decimals). 3. What is the t-cv? (exact value) 4. What is your conclusion? Only type "Reject" or Retain"

Alpha equals 0.01 level of significance for the given sample data.

. Dr. Hafen is doing research on the effects of study time (how many minutes students study) on test performance (their score on an exam).  He hypothesizes that the amount of study time will impact an individual’s performance on the exam.  Then Dr. Hafen collects data on 100 students.  He collects data on their ‘study time’ and their ‘exam performance’, then runs a Pearson correlation.  In your own words, please describe what Dr. Hafen’s null hypothesis would be and what Dr. Hafen’s alternative hypothesis would be.  If Dr. Hafen makes a Type I error, what would that mean in the context of this study?  If he makes a Type II error, what would that mean in the context of this study?