In this experiment, the two sets of data obtained from the same subjects were analyzed. First, the JNDs from the four subjects was pooled together and a repeated measures ANOVA analysis was performed. Then, Weber’s fractoin (JND/line length) was applied to the original data to compute the weber fraction and the same analysis test were performed. For this study, we were specifically interested on the data yielded from the Test of Within-Subjects Contrast and Effects and an ANOVA performed from our regression analysis. In addition, both sets of data were plotted to investigate whether the data would be consistent with previous studies. The Test of Within-Subjects Contrast and Test of Within-Subjects Effects for just the JNDs was not significant…
will be using 36 observations found from revenue 2006 to 2015 quarterly. The purposes for the regression analysis is to see if data has problems, test to make sure for the problem by visually and statistically, see the consequences for the problem, fixes that are available, and finally fix the problem to get better result in forecasting. Next using the BLUE which is minimizes the sum of square errors. This is a fitting the curve or ordinary least square and get rid of value in order to have…
For the first single linear regression (figure 1-3 and 1-4, associate’s and below), in order to test the question, it was useful for one to view a regression for educational levels under an associate degree because this is generally considered lower education. When looking at combined lower education with combined higher education, which is our second single linear regression (figure 1-5 and 1-6, bachelor’s and above), it was expected to see a correlation for both of them. The results were…
The Geographically Weighted Regression (GWR) method was used to interpolate climate characteristics at station level to spatial grids, generating both the interpolated value and the standard error estimation at each grid point. It is a localized regression based method widely used for spatial interpolation, accounting for the spatial inhomogeneity with spatially varying slopes and intercepts. At each prediction location, the GWR picks up nearby training data points and constructs a weighted…
Results Pearson-R Correlation The data underwent correlational analysis using the Pearson-R coefficient and obtained the following results: Table 1. N E O A C SPS Pearson Correlation .562** -.273** .022 -.294** -.218** Sig. (2-tailed) .000 .000 .676 .000 .000 N 372 372 372 372 372 ** Correlation is significant at the 0.01level (2-tailed) Based on the table above, the independent variables N (.562), E (-.273), A (-.294), and C (-.218) are significantly correlated to the dependent variable,…
Introduction to Regression Analysis Student Name Institution Regression analysis has been employed as serious evidence by lawyers and other individuals in the legal field. For instance, in the 1964 Civil Rights Act under Title VII, it was used to prove contract actions damages, biasness with regard to race in litigating death penalties and others. The difference between multiple and simple regression is that for multiple regression, earnings are affected by much more factors in…
focuses on analyzing historical data with a view of forecasting expected monthly sales. The case requires monthly sales to be projected, given the assumption that the actual monthly sales are correlated with the number of hits on the company’s website in the previous month. Consequently, the historical data on actual sales and number of hits are both used to forecast the expected sales over a period of three months. Notably, forecasting entails application of simple linear regression in order to…
relationship between the variables of interest. This can be described in numerous ways; this also depends on the analysis. This is concerned with how each variable is related to other similar variables. This association is based on the strength of the linear relationship in the degree of monotonicity. To the degree that it is based on counting various pairs in a relationship. Known as a statistical tool that investigates relationships among variables, regression analysis seeks to determine the…
great deal of negative publicity for the state’s public schools. It is important for educators, whether at the district level, research level, or policymaking level, to continue to study available data to identify areas of weakness with the realm of education and work collaboratively to remedy those issues. This report is a summary of several specific data sets collected by the Mississippi Department of Education and statistically analyzed for potential implications. This report will briefly…
Multiple Regression Analysis Question 1 The overarching objective is to assess the demographic variables that influence the perceptions of faculty members toward the organizational justice. In particular, the demographic variables include the occupation of the faculty members, rank, experience, and size. Various analyses are performed on the data, including descriptive and inferential analysis. Notably, the measures for occupation, rank, and the perceptions of faculty members are categorical…