This specific study was conducted using a hypothesis testing of two samples that had two means. The reason why the choice of testing of two samples means were because it compared the two sets of data that are directly related to each other. The reason why I believed that rural homes have a lower average of beds due to the fact that rural areas are the countryside rather than the big known towns or towns Of the State. The population that my data set represents was the number of beds that the in-patients had in each of the homes between non-rural home and rural home facilities.
The reason why the data was collected was because the Department of Health and Social Services of the State of New Mexico and over 60 licensed nursing facilities in New Mexico in 1988. The methods that were used to collect the data was by the number of beds that were used in the home, annual medical in patient days (hundreds), annual total patient days (hundreds), annual total patient care revenue (Sundress), annual nursing salaries ($hundreds), annual facilities expenditures ($hundred), and where the home was located between non-rural and rural areas.
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The source of the data set of the nursing home information toward New Mexico in 1 988 was part of the data analyzed by Howard L. Smith, Nell F. Poland, and Nancy Fisher. This was published in the Journal of Rural Health in winter 1992. This data set can be calculated in four different types of forms. It can be calculated in a health, consumer, medical, and economics perspective. With this statistical finding I used a hypothesis testing to figure out if rural homes have a lower average of beds was the two means hypothesis testing.
With this based it around a two-sample one-sided left-tailed test. With that being said I believe that rural nurse homes had a lower average use of bed. The claim that I came up with was the Pl pa while the alternative claim is Pl >= pa. The null hypothesis means that to a general statement or default position that there is no relationship between two measured phenomena. Alternative hypothesis reflects that there will bean observed effect for our experiment; it also tries to demonstrate in an indirect way by the use of the hypothesis test.
If you were to reject the null hypothesis that means that we are accepting the alternative hypothesis and this statement works vice versa. In this case that means that the null hypothesis can be rejected or disproving. For the data set that was given the null hypothesis also known as H-enough as Pl =pa, while the alternative hypothesis is Pl
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