Assignment 2: Statistical Methods In Healthcare

So, we should reject the null hypothesis H0. At a 0.05 level of significance level, we conclude that there is a significant difference between the average height for females and the average height for the males.

Create a research hypothesis tested using a one-tailed test and a research hypothesis tested using a two-tailed test.

When you perform a test of hypothesis, you must always use the 4-step approach: i. S1:the “Null” and “Alternate” hypotheses, ii. S2: calculate value of the test statistic, iii. S3: the level of significance and the critical value of the statistic, iv. S4: your decision rule and the conclusion reached in not rejecting or rejecting the null hypothesis. When asked to calculate p–value, S5, relate the p-value to the level of significance in reaching your conclusion.

If researchers conducted 9 t-tests on their study data. What alpha level should be used to determine significant differences between the two groups in the study? Provide your calculations.

The t-test is a parametric analysis technique used to determine significant differences between the scores obtained from two groups. The t-test uses the standard deviation to estimate the standard error of the sampling distribution and examines the differences between the means of the two groups. Since the t-test is considered fairly easy to calculate, researchers often use it in determining differences between two groups. When interpreting the results of t-tests, the larger the calculated t ratio, in absolute value, the greater the difference between the two groups. The significance of a t ratio can be determined by comparison with the critical values in a

One-sample t-test are used in the parametric test which analyzes the means of populations. The t-test for independent groups are statistics that relates difference between treatment means to the amount of variability expected between any two samples of data within the same population (Hansen & Myers, 2012). Critical values are used in significant testing provide a range of t distribution that is used in whether a null hypothesis is rejected. Based on the data below as the level of significance is at .05, thus the critical values would fall under ±1.860 and the t value for this is 1.871 would suggest for the null to be rejected as it is greater than the critical value (Privitera, 2015, p. 267). Based on the population mean of 70 there was a mean difference of

The t value that is the smallest represents health responsibility and is t = 1.03. It is not statistically significant, as the analyses did not indicate it to be so (i.e. no * next to the value).

1. In an experiment involving matched pairs, a sample of 15 pairs of observations is collected. The degree of freedom for the t statistic is 14.  true

A two-sample t-test is a hypothesis test that is used to compare if there is a difference between two groups. One of the first steps in a two-sample t-test is to establish a hypothesis. The two-sample test helps to answer hypotheses that question how the results of one group that may already be in place compare to the results of another group that is new. The two-sample hypothesis test is a common hypothesis test used in many industries.

The Bonferroni post-hoc analysis was used to test the pairwise differences of the adjusted means and the results were obtained as indicated in table 4 below.

Since this study lacked statistical power in determining significant correlations due our small sample size (N = 62), we emphasize the effect sizes of our results using Cohen’s d. We utilized independent samples t-tests

Assumption 2 of the t test is that there will be independence of observation. Here, a participant can only be a member of the male group or the female group; this cannot overlap and a person can only be assigned to one group. This will not be tested via a visual component, as this assumption is based on setting up the research correctly.

After the process had taken place of gathering all the required measurements we then carried out a statistical analysis which included the mean averages, the standard deviation and finally the t test using the primary data we had gathered. The software used was OpenOffice.org Calculator, this software is very similar to that of Microsoft Excel.

Answer (b): The t tests tell us if the predictor variable has a significant linear association with the outcome variable or not. The alpha value of 0.05 is used; if the value of

A one sample t test compares the mean of one group against a given, known value. For example, comparing the mean height of 10 students to value 165 cm.