Olivia sees that in her data there is a relationship between regular exercise and a rangeof health outcomes, with those doing exercise having better outcomes. Olivia canclaim which of the following statementsA. there is evidence of a correlation between regular exercise and health outcomes inher group of UTS academicsB. there is evidence of a causal relationship between regular exercise and healthoutcomes in the population of UTS academicsC. there is evidence of a causal relationship between regular exercise and healthoutcomes in her group of UTS academicsD. there is evidence of a correlation between regular exercise health outcomes inthe population of UTS academicsO She can claim only statement AO She can claim only statement CShe can claim all statementsO She can claim statements A and CO She can claim statements A and DShe can claim statements B and C

The question states that there is a relationship between regular exercise and a range of health…

Answered: Olivia sees that in her data there is a…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Similar questions

Which of the following is true regarding the difference between an observational study and an experiment? An experiment must have a control group while the observational study does not. An observational study is used for human subjects while an experiment is used for non-human subjects. In an experiment, the investigator randomly places subjects into treatment and control groups while in an observational study, no treatments are administered. The observational study can produce causal results while an experiment can only identify an association. None of these is true.
The data provides information on life expectancy and the number of televisions per thousand people in a sample of 22 countries, as reported by the world almanac and book of facts 2006 A. Describe the Direction and strength of the correlation between the two variables B. Because of the association between the variables, someone might mistakenly conclude that simply sending televisions to the countries with the lower life expectancies would cause their inhabitants to live longer. Comment on this argument and the reason televisions are likely associated with longer life expectancies C. In general, if two variables are strongly associated, does it follow there must be a cause and effect relationship between them? Explain
Which of the following correlations represents the strongest association between two variables: Group of answer choices A).50 B)-.20 C).00 D)-.85
Over the course of a year, you find a strong, positive correlation between ice cream sales and pool drownings in a medium-sized city. The mayor decides that to prevent drownings, ice cream will be banned within the city limits. However, you show the mayor that after controlling for the high temperature of each day, the correlation between ice cream sales and number of drownings drops to zero, because that relationship was actually: Group of answer choices direct. interactive. mediating. spurious.
Consider the following scenario and answer the questions below: The ornithologist decided to investigate the effect of temperature on the migration of North American birds. Develop a hypothesis in the appropriate format. Identify the independent variable. Identify the dependent variable. Plan an investigation (what would she do to collect data?). Did she engage in basic science or applied science? Explain. Did she engage in inductive or deductive reasoning? Explain
A non-spurious relationship implies that: Select one: A. there is a potential causal link between the independent and dependent variables. B. the relationship would not be maintained if relevant variables were controlled in the research. C. the explanatory power of the independent variable is due to error. D. the dependent variable is, in fact, the control variable.
There is a strong correlation between the number of students graduating from SVS and the population of squirrels in York Region. The most likely type of causal relationship is:A.cause and effect B.accidental C.presumed D.reverse cause and effect
even though we may observe a strong relationship between the explanatory and response variables, a lurking variable may also influence the response vatiabke. This is reffered to as A. correlation B. confounding C.association D. causation
If when measuring two quantitative variables on an individual, we find that increases in the first variable x correspond to decreases in the second variable y, we say that A. there is a positive association between the two variables. b. there is a negative association between the two variables. c. there is no correlation between the two variables. d. there is a cause-and-effect relationship between the two variables.
Correlation studies are often used to help determine whether certain characteristics are controlled more by genetic influences or by environmental influences. These studies often examine adopted children and compare their behaviors with the behaviors of their birth parents and their adoptive parents. One study examined how much time individuals spend watching TV (Plomin, Corley, DeFries, & Fulker, 1990). The following data are similar to the results obtained in the study. a. Compute the correlation between the children and their birth parents. b. Compute the correlation between the children and their adoptive parents. c. Based on the two correlations, does TV watching appear to be inherited from the birth parents or is it learned from the adoptive parents?
Does "correlation imply causation"? Give one example in which a variable X ispositively correlated with another variable Y, but we cannot deduce that X causes Y.
We discuss how to test for an association between two categorical variables in Section 6.8. A marine research team records the number of fish from 3 species that they find at different depth categories in the ocean. They are interested in assessing whether or not there is a relationship between the depth category (close to surface, mid-level, ocean floor) and the fish species found (species A, species B, species C). A two-way table showing the classification of a sample of 150 observations is given below. If the variables for the ocean depth category and the species are independent, how would you calculate the expected number of fish that are at the mid-level and from species C? Expected number =

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