Researchers conducting a study of 15 children with a diagnosis of ADHD wish to assess whether the BMI of the children is correlated with degrees of hyperactivity in the child. The BMI of the children is shown in the image. What is the value of the smallest mode in this data? (hint: there may be more than one mode - answer with the smallest one)

Select the statistic test that best fits each description. Study examing how much of the variation in blood pressure reading as explained by the variation in test scores       A. T-test independent samples B. T-test dependent samples C. One-way ANOVA D. Correlation E. Simple Regression

The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.707. At & = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho:p = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)

A correlation Study provides the following data r= -0.74 and the study involved 62 participants. What is the effect size ???

A hospital found that a lower outside temperature indicates a higher number of patient visits. What can we determine from this information?   There is no correlation between outside temperature and number of patient visits.   There is a correlation between outside temperature and number of patient visits. However, there is no causation. This is because there is an increase in the number of patient visits with a decrease in the temperature outside.   There is a correlation between outside temperature and number of patient visits. There may or may not be causation. Further studies would have to be done to determine this.

please answer blank questions only and or ones with a red x next to them.

14.36 Ecological correlation. Many studies reveal a positive correlation between income and number of years of education. To investigate this, a researcher makes two plots. Plot 1: Plot the number of years of education (the explanatory variable) versus the average annual income of all adults having that many years of education (the response variable). Plot 2: Plot the number of years of education (the explanatory variable) versus the individual annual incomes of all adults (the response variable).

Can you help me out by showing me an example of a weak positive correlation scatter plot? with a relistic example that shows the two variables that demonstrate this pattern?

You need to use Stata to look up the dataset and its variables. Use Stata Companion Textbook. (Dataset: NES. Variables: spend8, [pw=nesw].) The NES dataset contains spend8, which records the number of government policy areas where respondents think spending should be increased. Scores range from 0 (the respondent does not want to increase spending on any of the policies) to 8 (the respondent wants to increase spending on all eight policies). The NES, of course, polls a random sample of U.S. adults. In this exercise you will analyze spend8 using the mean and lincom commands. You then will draw inferences about the population mean. (Remember to specify nesw as the probability weight.) The spend8 variable has a sample mean of ______. Make sure you use [pw=nesw] so your results are nationally representative. There is a probability of .95 that spend8’s true population mean falls between a score of ______ at the low end and a score of ______ at the high end. A student researcher…

This question has 6 parts, Thank you.