Statistics Homework 4 Assignment 2015

| August 30, 2017

Question
1. Statistical inference is:

a. the act of generalizing from a sample to a population with calculated degree of certainty.

b. determining the range or interval in which the value of the parameter is thought to be.

c. investigating the validity of a claim about the value of a population characteristic.

d. Values of the test statistic for which we reject the null in favor of the alternative hypothesis.

2. A Type I error occurs when the null hypothesis is:

a. rejected and the research hypothesis is actually false.

b. rejected and null hypothesis is actually true.

c. accepted and research hypothesis is actually true.

d. accepted and null hypothesis is actually true.

3. Correlation is only a good statistic to use if:

a. the relationship is non-linear.

b. the relationship is roughly linear.

c. there is no relationship.

d. If the two variables increase or decrease together.

4. The non-parametric methods can be used when:

a. the data cannot be measured on a quantitative scale.

b. the numerical scale of measurement is arbitrarily set by the researcher.

c. the parametric assumptions such as normality or constant variance are seriously violated.

d. All of the above.

5. Suppose we want to estimate the average weight of an adult male in New York. We draw a random sample of 1,000 men and find that the sample mean is 180 pounds, and the standard deviation of the sample is 30 pounds. What is the 95% confidence interval?

a. 180 ± 3.0

b. 180 ± 5.88

c. 180 ± 30.0

d. 180 ± 1.86

6. Consider the following null and alternative hypotheses:

H0: p = 0.16

H1: p

8. At ? = 0.05 we conclude that:

a. the null hypothesis is not rejected.

b. the alternative hypothesis is rejected.

c. Can not decide.

d. The null hypothesis is rejected.

9. From this output and at ?=0.05 we conclude that:

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Sig.

weight

1.128

45

.04

1.965

45

.03

a. The population random variable is binomial distributed.

b. The population random variable is normally distributed.

c. The population random variable is not normally distributed.

d. The population random variable has no distribution.

The following SPSS output represent a nurses’ assessment (X) and physicians’ assessment (Y) of the condition of 10 patients at time of admission to a trauma center. Use the following SPSS output to answer questions (10,11)

Table (1)

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.912a

.831

.810

2.765

a. Predictors: (Constant), nurses

Table (2)

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

301.745

1

301.745

39.473

.000b

Residual

61.155

8

7.644

Total

362.900

9

Table (3)

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.211

2.056

.589

.572

nurses

1.082

.172

.912

6.283

.000

a. Dependent Variable: physicians

10. From table (2) and at ? =0.01 we conclude that:

a. the linear regression model is not appropriate for this data.

b. the relationship between physicians’ assessment and nurses’ assessment is not linear.

c. the linear regression model fits the data.

d. cannot reach a decision.

11. The predicted physicians’ assessment of a patient with nurses’ assessment 17 is:

a. 4.981

b. 18.394

c. 17.778

d. 19.605

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