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21 January, 04:34

A study involves three variables: income level, hours spent watching tv per week, and hours spent at home on the internet per week. list some ways the variables might be confounded. (select all that apply.) people with lower incomes might not own tvs or computers. people with higher incomes might not own tvs or computers. spending more time on-line might lead to spending less time watching tv. people with higher incomes likely will have high-speed internet access, which will lead to spending more time on-line. people who spend time at home on the internet never watch tv. incorrect: your answer is incorrect.

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  1. 21 January, 05:55
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    In statistics, a confounding variable or factor is that which affects both the dependent variable and other independent variables included in the model. In the model in the example, there are 3 explanatory or independent variables: income, tv, internet.

    From the options listed, these are the ones that can possibly be the cause behind the variables in the model acting as confounding factors:

    People with lower incomes might not own tvs or computers (the opposite is not likely to generate a pattern). People with higher incomes likely will have high-speed internet access, which will lead to spending more time on-line. People who spend time at home on the internet never watch tv.

    There are several ways in which the explanatory variables in the model can affect each other, apart from the dependent one.
  2. 21 January, 06:57
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    People with lower incomes might not own tvs or computers. Spending more time on-line might lead to spending less time watching tv.

    Explanation:

    In this study, we encounter three different variables. In order to ensure that these variables measure what we actually want them to measure, we need to make sure we do not have a confounding variable. A confounding variable is one that influences both the dependent variable and the independent variable. This could lead to a spurious association, which would make it difficult to interpret the data properly.
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