Conduct an evaluation of the organization based on strategic planning analysis, which includes the strengths and/or weaknesses that are internal to the organization and opportunities and/or threats external to the organization. 
October 17, 2018
List the treatmentsthat you would perform for each treatment session in the order that you would perform them. If you are combining treatments (e.g. Electrical stimulation & cryotherapy), place them in the same box.
October 17, 2018

analyze results and determine if a difference exists among groups of a study, a researcher might use various test to assist in examination of data (Erford, 2014). There are 4 various test used to determine whether there are differences among groups. Each test is used from the same type of equation yet they produce different results about statistical testing. (Erford, 2014)

t test– is a statistical test run to determine whether a statistically significant difference exists between two independent sample means. Example: Measuring the average diameter of shafts from a certain machine when you have a small sample. Dependent t test– like a t test, a dependent t test also compares two means but in this case the means are compared from the same sample of participants across time, such as with a pretest and post test administered to the same group. Example– A gym teacher gives you a physical exercise test in the beginning of the year. Throughout the year you work on improving your score. At the end of the year you retest. z-test– is used to compare a sample mean to a previously known population mean. It identifies whether there is a statistically significant difference between means of the sample and the population. Example: The teacher wants to compare students in her math class (the sample) to students in other math classes throughout the district (the population). The teacher will administer a standardized test with a given mean and standard deviation. The sample is greater than 30. ANOVA–  is an analysis of variance is a collection of statistical models used to analyze the differences among group means and their associated procedures. Example: A researcher wishes to know whether different pacing strategies affect the time to complete a marathon. The researcher randomly assigns a group of volunteers to either a group that (1) starts slow and then increases their speed, (2) starts fast and slows down or (3) runs at a steady pace throughout. The time to complete the marathon is the outcome (dependent) variable. ANCOVA– is used to nullify the effects of a confounding variable by statistically removing the variability in the dependent variable caused by the confounding variable. Example: pretest-posttest randomized experimental design, in which pretest scores are statistically controlled. In this case, the dependent variable is the posttest scores, the independent variable is the experimental/comparison group status, and the covariate is the pretest scores.]]>

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