Running heart rate - Jose is a physician who is researching to what extent running affects heart rate in 18-2b year-olds. He believis thit s 50% of 18-25 year-olds will experience a heart rate of more than 120 beats per minute (bpm) after running a mile. Jose recruits a random sample of 252 people between the ages of 18 and 25 to run a mile and records their heart rate. He finds that 98 have a heart rate of more than 120 bpm. Round all calculated answers to 4 decimal places. 1. Correctly state the null and alternative hypotheses. Hop ? HAP ? 2. If you assume that the observations in the sample are independent, what is the smallest value the sample size could be to meet the conditions for this hypothesis tent? OA 20 OB. 98 OC. 10 OD. 25 OE None of the above 3. Calculate the test statistic for this hypothesis test.

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Section10.6: Summarizing Categorical Data
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Running heart rate - Jose is a physician who is researching to what extent running affects heart rate in 18-25 year-olds. He believes that less than
50% of 18-25 year-olds will experience a heart rate of more than 120 beats per minute (bpm) after running a mile.
Jose recruits a random sample of 252 people between the ages of 18 and 25 to run a mile and records their heart rate. He finds that 98 have a heart
rate of more than 120 bpm.
Round all calculated answers to 4 decimal places.
1. Correctly state the null and alternative hypotheses.
Ho :p ? -
HA:P ?
2 If you assume that the observations in the sample are independent, what is the smallest value the sample size could be to meet the conditions for
this hypothesis tent?
OA 20
OB. 98
OC. 10
OD. 25
OE None of the above
3. Calculate the test statistic for this hypothesis test.
4. Calculate the p-value.
5. Which of the statements below are correct interpretations of the p-value? You should choose all that are correct interpretations
DA. The p-value is the proportion of times in repeated sampling that the alternative hypothesis is true.
OB. The p-value is the probability that the null hypothesis is true.
DC. This p-value suggests that based on this sample there is strong evidence that the nul model is not compatible with the data.
OD. This p-value suggests that based on this sample there is extremely strong evidence that the null model is not compatible with the data.
DE. If we repeat the hypothesis test many times, the p-value is the proportion of times our test statistic will be close to the expected value of the null
distribution.
OF The p-value is the probability of obtaining a sample result at least as or more in favor of the alternative hypothesis if the null hypothesis is true.
Transcribed Image Text:Running heart rate - Jose is a physician who is researching to what extent running affects heart rate in 18-25 year-olds. He believes that less than 50% of 18-25 year-olds will experience a heart rate of more than 120 beats per minute (bpm) after running a mile. Jose recruits a random sample of 252 people between the ages of 18 and 25 to run a mile and records their heart rate. He finds that 98 have a heart rate of more than 120 bpm. Round all calculated answers to 4 decimal places. 1. Correctly state the null and alternative hypotheses. Ho :p ? - HA:P ? 2 If you assume that the observations in the sample are independent, what is the smallest value the sample size could be to meet the conditions for this hypothesis tent? OA 20 OB. 98 OC. 10 OD. 25 OE None of the above 3. Calculate the test statistic for this hypothesis test. 4. Calculate the p-value. 5. Which of the statements below are correct interpretations of the p-value? You should choose all that are correct interpretations DA. The p-value is the proportion of times in repeated sampling that the alternative hypothesis is true. OB. The p-value is the probability that the null hypothesis is true. DC. This p-value suggests that based on this sample there is strong evidence that the nul model is not compatible with the data. OD. This p-value suggests that based on this sample there is extremely strong evidence that the null model is not compatible with the data. DE. If we repeat the hypothesis test many times, the p-value is the proportion of times our test statistic will be close to the expected value of the null distribution. OF The p-value is the probability of obtaining a sample result at least as or more in favor of the alternative hypothesis if the null hypothesis is true.
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