Learning Team Reflection Essay

Statistics refers to the use of numerical information in normal life to calculate facts and figures in limitless circumstances. In addition, statistics refers to the scientific collecting, classifying, summarizing, organizing, analyzing, and reading numerical data. This week the classs objectives were to apply the abuses in testing a research conjecture, to comp are the centre of dickens or much conferences, and to calculate the correlation betwixt devil variables. Learning aggroup Ds members have reflected on each of these issues and share their insights on these objectives.Testing a Research HypothesisThe purpose of testing a research hypothesis is to prove or disprove the research question. The number 1 timbre in testing a research hypothesis is to put in the problem in the form of a question. The second step is to kingdom the research question as it relates to the null hypothesis and alternative hypothesis. wherefore the parameters must be set to test the null hypo thesis. The fourth step is to calculate the probability of the test statistics or rejection region. Finally, the findings from the tests must be stated. The hypothesis was familiar to one group member, so she felt comfortable with the topic. She did non struggle with any particular topic this week. This weeks topics outright relate to her field of study. As an accountant it is important to have a good understanding of mean, median, and mode, as well as statistical probability. These topics are all a part of learning to analyze information and educate educated and well-thought business decisions.Compare the Means of Two or more GroupsThe experimental method of comparing the means of ii or more groups is a pretty common occurrence in statistical research. The cognitive operation for estimating and testing the hypothesis when using a single s group Ale nation will also apply in a case scenario with two or more groups or populations however, modifications are required for acc uracy. In former(a) words, the 5-Step Hypothesis Testing procedure is used with multiple s antiophthalmic factorle experiment, as well. Whenever the area of enkindle involves the differences, comparison, proportions or variability, then data stick out be collected on two or more groupsthis would be considered the scratch parameter (Lind, Marchal, & Wathen, 2011). In a quantitative analysis the interest is more likely to compare means or variances whereas, a soft experiment with two outcomes is more likely to focus on mastery or failure.When comparing the means of two or more groups these populations can both or all be independent and the expectation is to discover the reason for a difference in the meansthis would deliver a result where the means are other than zero. The typical assumption is that thither will be a normal dispersal and that a hit-or-miss sample is collected for each of the populations. Another characteristic of comparing means of two or more groups is t hat 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).Calculate the Correlation Between Two VariablesWhen calculating the correlation between two variables, the objective is to see how one variable is influenced by another(prenominal) variable. The bivariate alliance displays the connection between two variables (x and y) and correlation shows how to peak their relationship. The correlation is calculated using the coefficient of correlation. This measurement calculates the power between the two variables (x and y). (Coefficient correlation) The coefficient correlation will have limits between -1 and +1, and does nt rely on the initial values of x or y. The coefficient correlation would suggest the high the number, the higher the correlation, and the lower the number, the lower the correlation (but this is a linear correlation). A value of zero will indicate no correlation.In conclusion, the aggroup learned that once a hypothesis has been formed the next step is to test it for acceptance or rejection. An experiment must then be created to determine if the predictions were correct or not. In many situations the interest lies in discovering relationships between the means of two or more groups. T-tests and analysis of variance are widely used statistical methods to compare group means. Moreover, the squad learned how to calculate the correlation between two variables to determine the relationship or affect of one variable upon another. The correlation between two variables suggests that a change in one variable will feature a proportional change in the other variable.ReferenceLind, D. A., Marchal, W. G., & Wathen, S. A. (2011). Basic statistics for business and economics (7th ed.). New York, NY McGraw-Hill/Irwin.