Acct 3321 Final

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Levene’s test statistics is observed to be at 2.490 with p-value as 0.032 < alpha (0.05). Thus, we must reject Ho at 5% level and finalize that the variance errors of the dependent variable is not equal across the board (groups) .

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To test the significance of the intercept:H0: β0=0; H1: β0≠0. t (n-4) = ^β0- β0 / SE (^β0) = 2.89; p-value = 0.006 <0.05. The t-score is statistically significant. Therefore, we have sufficient evidence to reject the null hypothesis.

Continuing with the global test, the decision tool is not to reject the null hypothesis. The computed value of ‘f’ is less than or equal 5.41. If the computed value is more than 5.41 then we reject the Ho.

In addition, the cost of goods sold rate is 70% and the desired inventory level is 30% of next month’s cost of sales.

Based on hypothesize one the One-Sample T-Test Output is presented below. This output consists of two parts: one of them is One-Sample Statistics and the other one is One Sample Tests. Result from The One-Sample Statistics is explained as sample size is presented as (N), mean, standard deviation, and the standard-error-of-the-mean (the standard deviation divided by the square route of N) for each variable being tested. The test value is taken as 3.

If [pic]is the coefficient of determination for a regression [pic], then the square root of [pic] , [pic] is called the multiple correlation coefficient. Note that [pic] where [pic] is the sample variance of [pic], and that for large [pic], [pic].

From this analytic calculation it is clear that both the null and alternative hypotheses constitute a one-tailed test. The null hypothesis will be rejected if the sample mean is too small. For this analysis, the significance level is 0.01. The test method is a one sample t-test.

The parameters β0 and β1 are constants describing the functional relationship in the population. The value of β1 identifies the change along the Y scale expected for every unit changed in fixed values of X (represents the slope or degree of steepness). The values of β0 identifies an adjustment constant due to scale differences in measuring X and Y (the intercept or the place on the Y axis through which the straight line passes. It is the value of Y when X = 0). ∑ (Epsilon) represents an error component for each individual. The portion of Y score that cannot be accounted for by its systematic relationship with values of X.

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This study was performed on 200 students are enrolled in the MBA program at Whatsamattu U. The variables in this study include their age, gender, major, GPA, Bachelors GPA, course load, English speaking status, family, and weekly hours spent studying. Furthermore, the outcomes of this data exhibit 50 students have undefined majors, 55 students major in Finance, 70 students major in Leadership and 25 students major in Marketing. In other words, the relative frequency of students enrolled, only 25% percent of students have no major, 27.5% of students major in Finance, 35% of students major in Leadership and 12.5% of student major in Marketing. Therefore, the majors of these students are not statistically relevant to the participation in the

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Submission of this assignment/exam certifies my compliance with the UHCL Honesty Code that I signed at the start of the semester. I pledge on my honor that I have complied with this policy, inclusive of not acquiring unauthorized information or assistance, not providing others with unauthorized information or assistance, avoiding plagiarism, avoiding conspiracy, avoiding fabrication/falsification,

Submission of this exam/assignment certifies my compliance with the UHCL Honesty Code that I signed at the start of the semester. I pledge on my honor that I have complied with this policy, inclusive of not acquiring unauthorized information or assistance, not providing others with unauthorized information or assistance, avoiding plagiarism, avoiding conspiracy, avoiding fabrication/falsification, avoiding abuse of resources and materials, and reporting the academic dishonesty of others