Please help me understand how to solve question and understand properly. A researcher conducted a study about the hemoglobin levels among menopausal and non-menopausal women. With study of 20 women total, the following information was collected: Hemoglobin Level (g/dl), Age, and Menopausal Status (yes/no). The researcher conducted a multiple logistic regression analysis to find the effects of hemoglobin level, and age on menopausal status. The summary of the analysis is attached as photo.  Question: Determine the 95% confidence interval for the Odds Ratio for the hemoglobin level with interpretation.

A high correlation between two variables does not always mean that changes in one cause changes in the other. The best way to get good evidence that cause-and-effect is present is to

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?

A colleague of yours is completing a final report on the causes of the frequency of cyberbullying.  In this report, she is asked to identify the causes that most strongly impacted the frequency of cyberbullying.  She conducts an OLS regression.  What statistic do you advise her to use in her discussion?  Why?

What information does a regression coecient provide that a correlation does not?

Low-Density Lipoprotein (or LDL) is considered the "bad" cholesterol because it forms plaques in arteries, raising the risk for heart attack and stroke. Suppose you are interested in predicting LDL (in mg/dL) using one's age (in years). Assume that LDL levels and age are normally distributed and that the correlation between the two variables is 0.534. Based solely on the regression effect, a person whose age is at the 60th percentile is predicted to have an LDL level ____. [Source: Ldl cholesterol: Definition, risks, and how to lower it. (2020, March 09). Retrieved from https://www.webmd.com/heart-disease/ldl-cholesterol-the-bad-cholesterol]    Question 4 options:   A)  above the 60th percentile   B)  exactly at the 60th percentile   C)  exactly at the 40th percentile   D)  I need more information to answer this   E)  below the 60th percentile

The consumption function captures one of the key relationships in economics. It expresses consumption as a function of disposal income, where disposable income is income after taxes. The attached file "Regression-Dataset1" shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016. a)what is the Pearson correlation value between income and consumption? Select one: Ⓒa. 0.978 b. 0.109 c. None of the above d. 0.791

Help me please

Why do we need to study variability? Can you give a 'real life' example?

The consumption function captures one of the key relationships in economics. It expresses consumption as a function of disposal income, where disposable income is income after taxes. The attached file “Regression–Dataset1” shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016.  a)what is the Pearson correlation value between income and consumption?  Select one: a. 0.791 b. 0.109 c. None of the above d. 0.978