Df Sum SqMean Sq F-value p-valueX14393439324.166.65e-06Residuals6311455182Table 3: Q10) ANOVA table.Normal Q-QResiduals vs Fitted3708.802562°062TT-2-112505560657075Theoretical QuantilesFitted valuesIm(Y - X)Im(Y ~ X)Figure 4: Q10) QQ-plot.Figure 5: Q10) Residual plot.(a) What are the independent and dependent variables?(b) From the scatter plot, is there evidence that a linear regression would not besuitable for this dataset?(c) Use the regression summary to write an equation for the line of best fit.(d) At the ahas an impact on final mark? State the relevant null and alternative hypotheses.0.05 significance threshold, is there evidence that tutorial attendance(e) If I attend 3 more tutorials, what impact do I expect this to have on my finalmark?(f) Is there evidence of non-normality or unequal variance in the residuals? Whatdoes this lead you to say about the validity of the model?(g) The R2 value for the model fit was 0.11. Write a sentence about what thisrepresents with respect to the data.opo6o 00 odoO o o10 20 30O 0-Residuals-1Standardized residuals You have been asked to analyse a suspected relationship between tutorial attendanceand final marks for a university course. The latest set of data includes final marks Y(between 0 and 100) and tutorial attendance X (between 0 and 12) for 65 students.You have done a regression analysis on the dataset in R and the output is given below,along with a scatter plot of X and Y. Answer the subsequent questions regarding thisanalysis.8.24681012Tutorials AttendedFigure 3: Q3) Scatterplot of marks against tutorial attendance.Estimate Std. Errort value Pr(> |t|)(Intercept)44.15174.62079.5557.17e-14X2.79140.56794.9156.65e-06Table 2: Q10) Regression summary.0000000 00O O0 OOO 00O Oo o080940Final Mark

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MATLAB: An Introduction with Applications

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Publisher:Amos Gilat

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Jadual 2 : Ringkasan analisis korelasi kajian kemurungan dan kebimbangan Table 2 : The summary of correlational analysis of depression and anxiety . Correlations Depression Anxiety Pearson Correlation Depression Anxiety Sig (2-tailed) Depression Anxiety N Depression Anxiety 1.00 .282 - .003 112 112 .282 1.00 .003 - 112 112 Based on this position, write the likely regression equation. Write down statistics representation of the correlation in APA format.
The following table shows the starting salary and profile of a sample of 10 2 p employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of…
What variables do Teczar find have the most significant controlled associations with women in national parliaments?
You plan to fit a regression model that will be used to predict first-year college GPA (FYGPA) from high-school GPA (HSGPA), ACT score (ACT), first-generation status (Yes or No), socioeconomic class (lower class, lower to middle class, middle to upper class, and upper class), and school type (public or private). What is the total number of estimated regression coefficients? If the sample size is n = 250 students, what are the degrees of freedom for the following sources of variation: Regression Error Total
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill 13.45 + 4.39*Size Coefficients Estimate Std. Error (Intercept) 13.45 Size 4.39 0.54 0.2 We are 90% confident that the mean annual electric bill increases by between dollars and dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
In an ANOVA table for a multiple regression analysis, the global test of significance is based on the _________. Select one: a. Regression mean square divided by the mean square error b. Treatment mean square and block mean square c. Treatment mean square divided by the error variation d. Block and error variation
There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?
A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+???? Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 * 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq = 96.3% R-sq(adj) = 95.3%…

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