Questions and Answers on Critical Evaluation in Statistics - Paper Example

2021-07-08
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Answer: The question comes to mind, do we have enough power to make a determination and it was found that if N for each group is 30 or more that the sample size should be sufficient and acceptable to do the analysis.  The example size N= 65 for four face to face classes, and N = 69 four online classes with both appearing to be above 30.

Question 2: Critically evaluate the statements for meaningfulness.

Answer: When evaluating the statement for meaningfulness, it was found to be incorrect because the P value is too high .074 and there was no evidence found that prove they are in fact different. American Statistical Association (2016) states that by itself, a P value does not provide a good measurement of evidence regarding a model of hypothesis (p.1).

Question 3: Critically evaluate the statements for statistical significance.

As we look at the statements of statistical significance, there was no indication found that the two groups were found to be significantly different. The P- value is higher than .05 and no statistical significance exist when comparing the trivial difference (Frankfort-Nachmias & Leion- Guerrero 2015), illustrates that statistical hypothesis testing is a procedure that allows us to evaluate hypothesis and population parameters based on sample statistics (p.268).

Question 5: Based on your evaluation, provide an explanation of the implications for social change.

Answer: When looking at whether social changes can be impacted by this study, it does not show much of an impact on social changes because the differences between the groups are not significant and the study does not show higher levels of satisfaction either way.

SCENARIO # 3

A t-tests statistical significance indicates whether or not the difference between two groups averages most likely reflects a real difference in the population from which the groups were sample.

Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful? An independent samples t test was conducted to determine whether differences exist between men and women on cultural competency scores. The samples consisted of 663 women and 650 men taken from a convenience sample of public, private, and non-profit organizations. Each participant was administered an instrument that measured his or her current levels of cultural competency. The cultural competency score ranges from 0 to 10, with higher scores indicating higher levels of cultural competency. The descriptive statistics indicate women have higher levels of cultural competency (M = 9.2, SD = 3.2) than men (M = 8.9, SD = 2.1). The results were significant t (1311) = 2.0, p

Scenario 3: Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?

Answer: Sample t test was conducted to find out what differences exist between the selected men and women regarding cultural competency and their scores. Deitz & Kalof (2009) illustrates how the different ways that we collect data leads to measurements with different characteristics, in quantitative research we always assign numbers to what we observe in the world (p.34).

Question 1: Critically evaluate the sample size.

Answer: When we look at the sample size of: 663=Women, and 650 = Men with scores ranging from 0 10, it was found to be sufficient and acceptable. The descriptive statistics for women were found to be sufficient and acceptable. The descriptive statistics for women were found to have a higher level of cultural competency (M= 9.2, SD = 3.2) then men (M = 8.9, SD = 2.1). Laureate Education (2016f) states that the results were significant t (1311) = 2.0, p <.05, indicating that women are more culturally competency than men (p.2).

Question 2: Critically evaluate the statements for meaningfulness.

Answer: Although there is a small difference between the groups, it could become statistical significance in the study if the levels were found to be a bit higher to make a real impact but with the study and results there were trivial differences in women testing higher on cultural competency than men.

Question 3: Critically evaluate the statements for statistical significance.

A statistically significant t-test result is one in which a difference between two groups is unlikely to have occurred because the sample happened to be atypical. Statistical significance is determined by the size of the difference between the group averages, the sample size, and the standard deviations of the groups. For practical purposes statistical significance suggests that the two larger populations from which we sample are actually different.

Question 4: Based on your evaluation, provide an explanation of the implications for social change.

Answer: The results of this study show that there is a difference in gender awareness of cultural competency. In order for social change to take place it must start with understanding that different cultures look at the other gender differently. Cultural change must begin in the schools, homes and work. Males and females need to understand that each one is equal.

 

SCENARIO # SAMPLE STATISTICS

Question 1: First Report; Critically evaluate One-Sample Statistics; Level of democracy: Today

Answer: The higher the standard deviation the lower the consensus on the level of democracy. The democracy values under consideration and widely dispersed. If the level of democracy values score were 1 to 10 then we can confidently conclude that the mean of 5.52 signify the level of democracy is above average. However the data is widely dispersed.

Question 2: Critically evaluate One-Sample T Test: Level of democracy: today

Answer: The p values are below 0.05 signifying that signifying that the level of democracy is very significant today. The negative confidence interval means that the level of democracy results were opposite of those expected. This means that a portion of the population believe that there is no democracy or is not applicable to them.

Question 3: T-Test Second Report; Critically evaluate group statistics: Level of democracy: today

Answer: The higher the standard deviation the lower the consensus on the level of democracy. The democracy values under consideration and widely dispersed. There was less consensus on the level of democracy in North Africa with a standard deviation of 3.092 than southern Africa with a standard deviation of 2.795. The difference in the level of democracy mean signify that there is more democratic space in southern Africa than in northern Africa. The level of democracy in North Africa is below average if the democracy values score lies between 1 to 10.

Question 4: Critically evaluate Independent Samples Test: Level of democracy: today: Equal variances assumed

Answer: The p values are below 0.05 signifying that level of democracy under Levenes test was significant. Thus I reject the null hypothesis of equal variances. This means there is a difference between the variances in the populations in North Africa and southern Africa. This means that the differences in sample scores from the mean did not occur on the basis of selecting samples by chance from population with similar variances.

Answer: Levenes test statistic makes conclusion and interpretation about data collected from the population. It accesses the similarity of variances, usually computed from a number of groups. Levenes tests the assumption that the sample population are similar. It tests the similarity of variance CITATION Lev60 \l 1033 (Levene, 1960). The two sample t test compares the equality of two population means CITATION Fie12 \l 1033 (Field, Miles, & Field, 2012). Testing for equality of means is simply testing for the difference in two or more population from which samples are drawn CITATION Urd01 \l 1033 (Urdan, 2001).

Question 5: Critically evaluate T test for equality of means;-

Answer:- The test statistic absolute value is 19.453 and is greater than the upper level confidence interval (0.967) beyond which we decline the null hypothesis and make a conclusion that the northern and southern Africa are different at 0.05 significance level.

SCENARIO # PAIRED SAMPLE STATISTICS

Question 1: Evaluate the Paired Samples Statistics: Pair 1:- T1: T2;

Answer: Then Scale of student's mathematics utility in T1 was not dispersed as much as in T2.

Answer: The paired sample statistics procedure used to determine if disparities of means of two sets of data is zero. Each entity is measured twice to give a pair of observations. Its application include case control studies or measure designs. Example include reviewing the effectiveness of tuition or a training program CITATION War12 \l 1033 (Warner, 2012).

Question 2: Critically evaluate the Paired Samples Correlations: Pair 1:- T1 & T2.

Answer: There is a positive correlation r=0.285 between T1 and T2 Scale of student's mathematics utility meaning an increase in T1 means there is an increase on T2 students mathematics utility. The correlation of T1 and T2 students mathematics utility is significant.

Answer: Correlation is the relation between two variables, it can be positive or negative. Positive correlation means variable scores move in the same direction when one variable is added the other variable behaves in a similar way. Whereas negative correlation is when one variable is enlarged and the other variable moves in an opposite direction. A correlation of zero means there is no correlation and a correlation represented by one means perfect positive correlation while correlation represented by -1 indicates perfect negative correlation CITATION Pal16 \l 1033 (Pallant, 2016).

Question 3: Critically...

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