Assignment SPSS Word2

SPSS Assignment  Answers to Questions Question 1.

(a). The scatter plot of the two variables that are variable crate and variable variable educat treating crime rate as dependent variable is shown below. [ file from crime.sav]

(b). after superimposing a straight line on to the scatter plot that is using the linear fit method, the relationship roughly looks linear R sq linear of .066. Although it may be curving up slightly or there may be an outlier. But if we use the cubic fit method the values are more fitted because the value of R [.242] for the cubic fit method is higher than the linear fit.

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SPSS Assignment 

(c) From the Pearson’s correlation value we can say that, there is a perfect positive correlation between these variables, which is statically significant at the 5% level. Because the perason’s coefficient r is 1.

Correlations Correlations violent crime rate pct hs graduates violent crime rate[

Pearson Correlation

1

Sig. (2-tailed) N pct hs graduates

-.256 .070

51

51

Pearson Correlation

-.256

1

Sig. (2-tailed)

.070

N

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51

51

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SPSS Assignment 

(d) When the variable crate is correlate with variable educat  the result of this regression is Model Summary

Model

R

R Square a

1

.256

Adjusted R

Std. Error of the

Square

Estimate

.066

.046

430.724

a. Predictors: (Constant), pct hs graduates a

Coefficients

Model 1 (Constant) pct hs graduates

Unstandardized

Standardized

95% Confidence Interval for

Coefficients

Coefficients

B

B

Std. Error

Beta

t

Sig. Lower Bound Upper Bound

2152.347

832.477

2.585 .013

479.421

3825.273

-20.197

10.893

-.256 -1.854 .070

-42.087

1.693

a. Dependent Variable: violent crime rate

(E) plot of the standardized residual against the predicted values in order to detect any outliers and to assess whether the relationship is linear and whether the residual variance is constant

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SPSS Assignment  There is one residual greater than 4 and the trend indicates that there is approximately a linear relationship between crime rate and education. And from the scatter of points that tends to increase a little as the predicted value increases which indicating that the assumption of constant variance may not be appropriate. Question2.

The data file for question 2 is in the country.sav which contains the demographic information of  122 countries. (a). Explore the relationship between the variable using a scatter plot. Dependent variable= lifeexpf  Independent variables= urban,docs,hospbed,gdp,and radio The result of the scatter plot matrix is shown below.

(b) The scatter plot matrix using the logarithm of the variables that don’t have a linear relationship is depicted below. Logarithm of the variables are= lndocs,lnbeds,lngdp, and lnradio As we can see easily from the scatter matrix plot the relationship is a linear relationship.

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SPSS Assignment 

(C) using the forward selection to find the subset of variables that best explain the dependent variable. Dependent variable= lifeexp Independent variables= lndocs,urban,lnbeds,lngdp,lnradio

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SPSS Assignment 

a

Coefficients

Standardized Unstandardized Coefficients Model 1

B (Constant) Natural log of doctors per 10000

2

(Constant) Natural log of doctors per 10000 Natural log of GDP

3

(Constant) Natural log of doctors per 10000 Natural log of GDP Natural log of radios per 100 people

Std. Error 57.232

.688

6.290

.318

42.138

3.206

4.261

.513

2.493

.519

41.697

3.140

4.123

.505

1.871 1.684

Coefficients Beta

t

Sig.

83.233

.000

19.792

.000

13.143

.000

.596

8.307

.000

.345

4.802

.000

13.278

.000

.577

8.168

.000

.566

.259

3.306

.001

.679

.142

2.482

.015

.880

a. Dependent Variable: Female life expectancy 1992

Number of doctors, GDP and number of radio are all positively related to life expectancy in females after controlling for the other variables. (d) The cook’s distance against the variable sequence Dependent variable= lifeexp Independent variable = lndocs,lngdp,lnradio As we can see from the result of the plot of the matrix of the cook’s distance the most influential countries are Chad, Afghanistan, an d Guinea.

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SPSS Assignment 

(e) The distribution of the standardized residuals is shown below With some possible outliers we can say that the distribution is normally distributed with the normal distribution.

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SPSS Assignment 

Question 3.

(a) (b) (c) (d) (e) (f) (g)

Independent sample T test Independent sample T test Paired T test Paired T test Independent T test Paired test Independent T test

Question 4. In the SPSS statistics box gives us the mean and standard deviation for each of the groups in this case age. It also gives the number of people in each group (N). Always check these values first.

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SPSS Assignment  The first section of the Independent Samples Test output box gives us the results of Levene’s test for equality of variances. This tests whether the variance (variation) of ages for the two groups (populations) is the same. The outcome of this test determines which of the t-values that SPSS provides the correct one is. Since the significance value from the output [.82] is larger than .05 it should be the first column of the out table to be used, which is Equal variance is assumed. In the given the output from the question, the significance level for Levene’s test is .82. This is larger than the cut-off of .05. This means that the assumption of equal variances has not been violated; therefore, when it is reported the t-value used is the one in the first column from the output. From the out table the value of  sig(2-tailed) in the first column is .000 less than .05 the required cut off there is a significance difference in the population’s mean ages of the two groups.

The value of t from the output table from the equal variance assumed column 3.9 and the values for N1 and N2 is the same from the output table 100. Up on substituting the value of the Eta squared is .0713. Then according to the guideline( proposed by Cohen,1998) for interoperating this value are .01=small effect .06= moderate effect .14= large effect For this particular question the, which have the effect size of .0713, effect is in the range of  moderate and large. An independent sample test was conducted to compare the average ages of people who buy and who don’t buy a product. There is a significance difference in buying the product [mean 29.45,SD 15.56 and mean 38, SD 15.49];t(198)=-3.9,p