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A team of researchers are interested in the association between age (in years, the explanatory variable) and systolic blood pressure (mmHg, the outcome variable). The results of a simple linear regression of systolic blood pressure (sbp) on age are provided in the following output.
What is the interpretation of the coefficient for age?
A sample of 102 university students were asked to record the number of hours they spent on their phone each day. The data were positively skewed and a transformation using the natural logarithm was found to provide a more normal distribution. A summary of the log transformed variable is provided.
What is the geometric mean of number of hours students spent on their phones?
Your team has developed a new app to remind people to floss daily. In the general population, it is estimated that 25% of people floss daily. Your team believes that their new app can increase this proportion to 42%. You plan a study to compare two groups – those who do use the app with those who don’t use the app. Calculate the required number per group, assuming 90% power and an alpha of 5%, with equal sized groups.
A sample of 188 students were asked how many cups of coffee they drink per day. A density plot of the results is shown in the figure.
What method would you use to test the hypothesis that there is no difference in the number of cups of coffee consumed each day between undergraduate and postgraduate students?
The figure below represents correlation coefficients (in no particular order) of -0.39, 0.82, 0.48 and 0.05.
Which plot corresponds to a correlation of 0.48?
An exercise physiologist conducted a study to assess university students' dietary habits. He sampled 28 students to test the following null and alternative hypotheses:
H0: the mean daily energy intake of university students is not different from the recommended daily intake of 8700 kJ.
HA: the mean daily energy intake of university students differs from the recommended daily intake of 8700 kJ.
The mean daily energy intake of the students is 7491 kJ. You conduct a one-sample t-test and obtain a P-value of 0.0012. How do you interpret the P-value?
Your colleagues want to test the hypothesis that mothers with low socio-economic status (SES) deliver babies whose birthweights are lower than babies born in other areas. To test this hypothesis, records were obtained for a sample of 100 full-term, live-born births from the maternity ward of a hospital in a low-SES area.
The mean birthweight was found to be 3263g with a sample standard deviation of 684g. The 95% confidence interval for the mean birthweight was calculated as:
Obs Mean Std. Err. [95% Conf. Interval]
---------------------------------------------------------------
100 3263 68.4 3127.28 3398.72
From the Australia's Mothers and Babies report published in 2020, the mean birthweight of all liveborn babies born in Australia in 2018 was 3323g.
The next step is to perform a one-sample t-test to test whether the birthweights from this hospital has the same mean as the general population. What, if anything, can you tell your colleagues about the P-value they will obtain from the one-sample t-test?
There is no need to complete this question - it is an old version that should not have been included this year. This question will not be graded.
You are interested in the physical characteristics of males who attend university. In particular, you are interested in whether the average BMI of male university students is different from 25 kg/m2 (the BMI classification of overweight). After sampling 213 students, you conduct a one-sample t-test to test the following hypotheses:
H0: the mean BMI of male university students is 25 kg/m2 HA: the mean BMI of male university students is not 25 kg/m2
The R output appears below:
The Stata output appears below.
What is the P-value from this test?
The mean height from a random sample of men was found to have a confidence interval from 177.7cm to 179.5cm. How do you interpret this confidence interval?