Testing the Difference Between the Respondents Demographic Groups

We conduct an independent sample t-test using Excel, and obtain the following output (see t-test-height)

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

When examining the differences between two or more groups, you can use the analysis of variance which is known as ANOVA. This is a statistical technique that is used to compare the means or averages of more than two groups. There are three uses of ANOVA which are the one-way, the two-way and N-way Multivariate ANOVA. (Solutions, 2013) The determining factor when to use one of the “ways” is dependent upon how many “treatments” are used in the study. We use the term treatment because ANOVA originated in the 1920’s to test different treatments of fertilizers’ crop yields. ("Analysis of Variance," 2012, p. 2) Here, we will cover the one-way and the two-way ANOVA.

In a quantitative analysis the interest is more likely to compare means or variances; whereas, a qualitative experiment with two outcomes is more likely to focus on success or failure. When comparing the means of two or more groups these populations can both or all be independent and the expectation is to determine the reason for a difference in the means—this would deliver a result where the means are other than zero. The typical assumption is that there will be a normal distribution and that a random sample is collected for each of the populations. Another characteristic of comparing means of two or more groups is that when standard deviation is known or unknown and the population sample is large, then a z distribution (z-test) is used and in the case where it is unknown and the sample size is small, then a t distribution (t-test) is used. However, in the case where the experiment calls for a test of two or more dependent samples for one group or population, then a paired t-test is used to draw results (Lind, Marchal, & Wathen, 2011).

8.4: Evaluate the impact of different factors including gender, age, ethnicity, and class on groups and individuals during this time period and impact these groups and individuals have on the events of the time.

Analysis of variance is a statistical method used to test differences between two or more means. ANOVA is used to test general rather than specific differences among means. An ANOVA conducted on a design in which there is only one factor is called a one-way ANOVA. The One-Way ANOVA is considered an omnibus test because it indicates whether or not there are any significant differences in the means between any of the groups. However, it does not indicate which mean are different. The One-way ANOVA compares the means of the samples or groups to make inferences about the population means. The one-way ANOVA, two kinds of variables: independent and dependent. Also, the one-way ANOVA is used to determine whether there are any statistically

One Way ANOVA is used to check if there is any significant various among the means of 3 or more unlinked groups. It fundamentally tests

At the .01 significance level is there a difference in the mean amount purchased on an impulse at the two stores? Explain these results to a person who knows about the t test for a single sample but is unfamiliar with the t test for independent means.

We conduct an independent sample t-test using Excel, and obtain the following output (see sheet T-TEST)

The type of t-Test is level to the variance, the independent t-test two groups are discrete and is exclusive due to the number (15) in each group, and the variance of the two groups is equal.

A t test is used to evaluate statistically significant differences among two samples (Creighton, 2007). For this assignment, I decided to test the following hypothesis and null hypothesis:

For this independent t test, the mean GPAs of 64 females and 41 males were compared. The variables used are (1) gender, and (2) GPA. The predictor, or independent, variable is gender. And the outcome variable is GPA. Gender can only have two values, male or female; this

There is a one way method and a two way method for an ANOVA analysis that can be used by the researcher. There is only one factor for the researcher to test for equality of the presented information in the one way method, and the two way mwthod allows for distinguishing if there may be another factor.

Pakistan’s Banking sector was selected for this research. Calmative is the nature of this study. Open

Data captured for this study, were analyzed through descriptive and inferential statistical methods. The descriptive analysis involves the use of percentage, tabulation presentation. While the inferential statistical method involved the used of the chi-square. The functions of fraud prevention, detection and control are interwoven, as the three works together to eliminate fraud and fraudulent tendencies. Therefore, internal control is highly significant in fraud detection and preventions in banking sector.