Scenario A. The manager at Dunder-Mifflin Paper Company interested in understanding if a company's employee benefits inc
Posted: Thu Jul 07, 2022 11:29 am
Scenario A. The manager at Dunder-Mifflin Paper Company interested in understanding if a company's employee benefits increase employee satisfaction. In 2020 the company implemented a new benefits package that included optional benefits such as childcare, eldercare, and retirement packages. The manager compares the employee satisfaction ratings from before and after the new benefits package was implemented and expects that satisfaction will be higher after the new package is implemented. What would be a type I error for this scenario? See the example question for guidance!
Here's an Example to give you an idea about what you'll be doing: A researcher is interested in testing whether a new therapy for adolescent depression works to reduce depression. He measures depression before and after the therapy and he expects depression levels to decrease after therapy. Hypotheses: Null Hypothesis: Ho: depression after therapy ≥ depression before therapy (in other words, depression is the same or worse after therapy than it was before therapy); Alternative Hypothesis: H₁: depression after therapy < depression before therapy (in other words, depression is lower after therapy than it was before). This hypothesis is directional • Type I error: The researcher concludes that depression decreases after therapy, when in reality depression is the same or worse after therapy (in other words, the researcher concludes that the therapy works to reduce depression, when in reality it did not!). • Type Il error: The concludes that depression levels are the same after therapy, when in reality they get better (in other words, the researcher concludes that the therapy did not work to reduce
IV depression before therapy (in other words, depression is the same or worse after therapy than it was before therapy); Alternative Hypothesis: H₁: depression after therapy < depression before therapy (in other words, depression is lower after therapy than it was before). This hypothesis is directional • Type I error: The researcher concludes that depression decreases after therapy, when in reality depression is the same or worse after therapy (in other words, the researcher concludes that the therapy works to reduce depression, when in reality it did not!). Type Il error: The concludes that depression levels are the same after therapy, when in reality they get better (in other words, the researcher concludes that the therapy did not work to reduce depression, when in reality it did!)
Here's an Example to give you an idea about what you'll be doing: A researcher is interested in testing whether a new therapy for adolescent depression works to reduce depression. He measures depression before and after the therapy and he expects depression levels to decrease after therapy. Hypotheses: Null Hypothesis: Ho: depression after therapy ≥ depression before therapy (in other words, depression is the same or worse after therapy than it was before therapy); Alternative Hypothesis: H₁: depression after therapy < depression before therapy (in other words, depression is lower after therapy than it was before). This hypothesis is directional • Type I error: The researcher concludes that depression decreases after therapy, when in reality depression is the same or worse after therapy (in other words, the researcher concludes that the therapy works to reduce depression, when in reality it did not!). • Type Il error: The concludes that depression levels are the same after therapy, when in reality they get better (in other words, the researcher concludes that the therapy did not work to reduce
IV depression before therapy (in other words, depression is the same or worse after therapy than it was before therapy); Alternative Hypothesis: H₁: depression after therapy < depression before therapy (in other words, depression is lower after therapy than it was before). This hypothesis is directional • Type I error: The researcher concludes that depression decreases after therapy, when in reality depression is the same or worse after therapy (in other words, the researcher concludes that the therapy works to reduce depression, when in reality it did not!). Type Il error: The concludes that depression levels are the same after therapy, when in reality they get better (in other words, the researcher concludes that the therapy did not work to reduce depression, when in reality it did!)