Mediterranean Diet and Cancer Risks

Mediterranean Diet and Cancer Risks

Mediterranean Diet and Cancer Risks

Flag this Question Question 222 pts Suppose a researcher discovers that length of time spent following a Mediterranean diet is negatively correlated with risk of developing cancer. Which of the statements logically follows from this information?
Eating a Mediterranean diet reduces the risk of developing cancer.
People who ate a Mediterranean diet for more time were more likely to have cancer.
Eating a Mediterranean diet increases the risk of developing cancer.
People who ate a Mediterranean diet for more time were less likely to have cancer.

Flag this Question Question 232 pts Figure: Student-Faculty Ratio

Reference: Figure 1
(Figure: Student–Faculty Ratio) The relation depicted in the scatterplot is potentially deceptive because of:
poor validity.
poor reliability.
the presence of outliers.
restriction of range.

Flag this Question Question 242 pts Assume that the correlation coefficient between class attendance and number of problems missed on an exam is (–0.77). Which statement regarding this finding is correct?
There is definitely no causal relationship between the two variables.
The correlation provides definitive information pertaining to causation.
If you attend class regularly, you are more likely to do well on the exam than someone who does not attend class regularly.
If you start attending class more regularly, the number of problems you miss on the next exam is certain to be reduced.

Mediterranean Diet and Cancer Risks

Flag this Question Question 252 pts The Pearson correlation coefficient is symbolized:
x
r
c
t

Flag this Question Question 262 pts The ________ quantifies the relationship between two variables.
magnitude of the correlation
sign of the correlation
correlation coefficient
correlation

Flag this Question Question 272 pts A ________ is a graphical representation of the relation between two variables.
polygon
correlation coefficient
scatterplot
histogram

Flag this Question Question 282 pts The proportionate reduction in error is a measure of the:
correlation between two variables.
variability of the dependent measure.
amount of variance in the dependent variable explained by the independent variable.
slope of a regression line.

Flag this Question Question 292 pts With regression we are concerned about variability around the ________, rather than variability around the ________ which would be the case in t tests or ANOVAs.
line of best fit; mean
median; tails of the distribution
mean; outliers
outliers; line of best fit

Flag this Question Question 302 pts To determine the slope of the line of best fit using the z-score regression information, we compare the values of:
X at zero versus X at 1.0.
X at zero versus Y at zero.
Y at zero versus X at zero.
Y at zero versus Y at 1.0.

Mediterranean Diet and Cancer Risks

Flag this Question Question 312 pts The regression line is also called the:
prediction estimate.
error of estimate.
line of best fit.
line of central limit.

Flag this Question Question 322 pts If we have information about the slope of the line of best fit that corresponds to two sets of data about class grades for different instructors, we cannot make comparisons based on these slopes because:
they are based on different populations.
slopes cannot be compared meaningfully.
they are not on a common scale.
the slopes have to share the same sign.

Flag this Question Question 332 pts Every year it seems as though last season’s baseball rookie of the year fails to live up to expectations for his sophomore season. What might explain this phenomenon?
regression to the mean
standard error of the estimation
overestimation of effect size
proportionate reduction in error

Flag this Question Question 342 pts Multiple regression predicts scores on a single ________ from scores on more than one ________.
dependent variable; independent variable
scale variable; nominal variable
independent variable; predictor variable
predictor; dependent variable

Flag this Question Question 352 pts As the standard error of estimate becomes larger, predictions become:
less accurate.
more accurate.
smaller.
larger.

Flag this Question Question 362 pts Proportionate reduction in error is sometimes called:
coefficient phi.
correlation coefficient.
alpha coefficient.
the coefficient of determination.

Flag this Question Question 372 pts A researcher calculates a standardized regression coefficient on data from 52 events and computes ? as 0.274. Assuming a two-tailed hypothesis test of the relation between these two variables is being conducted with an alpha of 0.05, what are the critical cutoffs?
–0.288 and 0.288
–0.273 and 0.273
–0.361 and 0.361
–0.250 and 0.250

Mediterranean Diet and Cancer Risks

Flag this Question Question 382 pts The measure of effect size used with regression is:
R2, just like with ANOVA.
the proportionate reduction in error, r2.
the alpha coefficient.
standard error of correlation.

Flag this Question Question 392 pts Which of the following statistics quantifies the improvement in ability to predict a person’s score when using the regression line rather than the mean?
standard deviation
proportionate reduction in error
standard error of the estimation
slope

Flag this Question Question 402 pts The standardized regression coefficient is not equal to the correlation coefficient when:
both variables are measured on an interval scale.
there is greater variability in the X variables compared to the Y variable.
the equation includes more than one independent variable.
a negative relationship is present.

Flag this Question Question 412 pts In a study designed to predict blood cholesterol levels from amount of daily saturated fat in grams (X1) and number of hours of daily exercise (X2), we determine that the slope of X1 is 5, the slope of X2 is –4, and the y intercept is 130. Which of the following formulas is the regression equation for these data?
? = 130 + 5(X1) – 4(X2)
? = 130 + 5(X1) + 4(X2)
? = 130 + 1(X)
? = 130 – 5(X1) – 4(X2)

Flag this Question Question 422 pts The standardized regression coefficient expresses the:
likelihood of rejecting the null hypothesis with a regression analysis.
relation between the independent and dependent variable in terms of squared units.
strength of the correlation between the two variables that are now incorporated into a regression analysis.
predicted change in the dependent variable in terms of standard deviation units as a result of a 1 standard deviation increase in the independent variable.

Flag this Question Question 432 pts The standardized regression coefficient is often called a:
normalized regression.
beta weight.
weighted estimate.
estimate of best fit.

Mediterranean Diet and Cancer Risks

Flag this Question Question 442 pts The regression line is the line that:
minimizes the correlation coefficient.
is the mean of the dependent variable.
minimizes error in predicting scores on the independent variable.
minimizes error in predicting scores on the dependent variable.

Flag this Question Question 452 pts The standardized regression coefficient expresses a predicted change in the dependent variable in terms of:
error units.
slope.
a 1-unit change in the independent variable.
standard deviations units.

Flag this Question Question 462 pts We can examine a graph to get a sense of how much error there is in a regression equation. Which of the following describes a graph that reveals there will be a high amount of error when using our regression equation?
Data points cluster very close to the line with several outlier exceptions.
The data points consistently cluster far away from the line of best fit.
Data points cluster close around the line of best fit.
Data points fall directly on the line.

Flag this Question Question 472 pts In the equation ? = 98 + 4.30(X1) + 7.20(X2), what is the slope?
98
4.30
Both 4.30 and 7.20 are slopes.
7.20

Flag this Question Question 482 pts In the equation for a regression line, the intercept is the:
predicted value for Y when X is equal to 0.
value for X when Y is equal to 0.
z score of the amount that Y is predicted to increase as X increases.
amount that Y is predicted to increase for a one-unit increase in X.

Flag this Question Question 492 pts In a study designed to predict blood cholesterol levels from amount of daily saturated fat in grams (X1) and number of hours of daily exercise (X2), we determine that the slope of X1 is 5, the slope of X2 is –4, and the y intercept is 130. If someone reports that she typically eats 10 grams of saturated fat daily and exercises 1 hour daily, what would you predict for the person’s cholesterol level?
184
180
176
150

Flag this Question Question 502 pts A small standard error of the estimate means that:
your two variables are poorly correlated.
confounding variables may be present.
variability is high in your Y variable.
you are making predictions with great accuracy.

Mediterranean Diet and Cancer Risks

Flag this Question Question 512 pts The table includes information for creating a regression equation to predict students’ attitude toward statistics from their attitudes toward Britney Spears and beer.

Table: Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 4.974 0.590 8.432 0.000
attbritneyspears 0.264 0.155 0.256 1.701 0.097
attbeer -0.309 0.122 -0.381 -2.536 0.015
a Dependent variable: attstatistics Reference: Table 1
(Table: Coefficients) What is the y intercept for this problem?
0.590
0.000
4.974
8.432

Flag this Question Question 522 pts The table includes information for creating a regression equation to predict students’ attitude toward statistics from their attitudes toward Britney Spears and beer.

Table: Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 4.974 0.590 8.432 0.000
attbritneyspears 0.264 0.155 0.256 1.701 0.097
attbeer -0.309 0.122 -0.381 -2.536 0.015
a Dependent variable: attstatistics Reference: Table 1
(Table: Coefficients) Was either variable a significant predictor for attitude toward statistics?
Attitude toward Britney Spears was a significant predictor but attitude toward beer was not.
No; neither was a signigicant predictor.
Yes; both were significant predictors.
Attitude toward beer was a significant predictor but attitude toward Britney Spears was not.

Flag this Question Question 532 pts If two variables, independently, can help us predict the outcome of a third variable, we say that they are:
orthogonal.
autonomous.
standardized.
proportionate.