Questions and Answers on US Health Care Statistics

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.

Cohen’s paper The Earth is Round (p>0.05) is a critique of null-hypothesis significance testing (NHST). In his article, Cohen presents his arguments about what is wrong with NHST and suggests ways in which researchers can improve their research, as well as the way they report their research. Cohen’s main point is that researchers who use NHST often misinterpret the meaning of p-values and what can be concluded from them (Cohen, 1994). Cohen also shows that the NHST is close to worthless. NHST is a way to show how unlikely a result would be if the null hypothesis were true. A Type I error is where the researcher incorrectly rejects a true null hypothesis and a Type II error is where the researcher incorrectly accepts the false null

|A random group of apartments was selected from a city to analyze the number of bedrooms they have. Is there evidence to reject |

The health status of the population in the United States is a national priority. The Healthy People 2020 outlines priorities and to improve the health of individuals and communities across the country. Healthy People 2020 is defined as a comprehensive set of national objectives for “improving the health of all Americans” (Healthy People 2020, n.d, para. 1). The Healthy people 2020, is aimed at improving the health of individuals and communities and envisions “a society in which all people live long, healthy lives” (Healthy People 2020, n.d, para 4). A short priority list was developed and contains twenty-six objectives knowns as Leading Health Indicators (LHI). The list of objectives was created to prioritize health issues that must be addressed and to find appropriate actions to take in order to improve the health of the population.

Because the p-value of .035 is less than the significance level of .05, I will reject the null hypothesis at 5% level.

Data that is statistically significant helps us to understand whether there is a relationship within the null hypothesis. T statistical significant results showed that the participants who consumed caffeine performed worse than participants who did not was less than 5% (p < .05). This means for the author to determine whether a test is significant it must be less than .05, which is the significance level. The P value (probability value) is defined as the probability of obtaining a result equal to or "more extreme" than what was observed (Wikipedia). A p-value helps determine the significance

Given the following information, would your decision be to reject or fail to reject the null hypothesis? Setting the level of significance at .05 for decision making, provide an explanation for your conclusion.

4. In a well-designed study, what does it mean to say there is a statistically significant difference between groups?

The 13 hypotheses listed in the Literature Review section were statistically tested. Each hypothesis is again listed below along with the

Two studies are conducted to compare the experiences of seniors living in high-rise public housing to those of seniors living in townhouses with subsidized rent. The first study interviews 40

It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.

To test the null hypothesis, if the P-Value of the test is less than 0.05 I will reject the null hypothesis.

“Hypothesis testing is a decision-making process for evaluating claims about a population” (Bluman, 2013, p. 398). This process is used to determine if you will accept or reject the hypothesis. The claim is that the bottles contain less than 16 ounces. The null hypothesis is the soda bottles contain 16 ounces. The alternative hypothesis is the bottles contain less than 16 ounces. The significance level will be 0.05. The test method to be used is a t-score. The test statistic is calculated to be -11.24666539 and the P-value is 1.0.  The P-value is the probability of observing a sample statistic as extreme as the test statistic, assuming the null hypothesis is true. The T Crit value is 1.69912702. The calculations show there is enough evidence to support the claim that the soda bottles do

Conclusion : Fails to reject the null hypothesis. The sample does not provide enough evidence to support the claim that mean is significantly different from 12 .

With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.