
1.
An air quality analyst measured the average wind speeds (taken at 7:00 a.m. and 10:00 a.m.) at an airport for a week (seven days). The correlation coefficient between day number and average wind speed for this particular dataset is r = 0.13. Which of the following best describes the strength of this linear correlation?

2.
A nuclear scientist studying the decay of a highly radioactive substance noted that the correlation coefficient between the amount of the substance remaining at time {eq}x {/eq} and time {eq}x {/eq} is r = 0.01. Which of the following statements is/are always true based on this computed value of r?
I. The strength of the linear correlation between the amount of substance remaining and time is extremely strong and negative.
II. The strength of the linear correlation between the amount of substance remaining and time is negligible.
III. The strength of the linear association between these two variables is negative.

3.
A woman who is interested in measuring the association between height and weight among female citizens of a certain country obtained an estimate of r = 0.9955 based on a dataset gathered for this purpose. This association is _____.

4.
The coefficient of linear correlation between a company's firstquarter sales from 19411950 and its firstquarter sales 40 years later, i.e., from 19811990, is r = 0.12. The strength of the linear association between these two variables is best described as a _____.

5.
A plant geneticist noted that the coefficient of linear correlation between petal lengths and sepal widths in Iris setosa, a certain species of the iris flower, is r = 0.18, based on a sample obtained for this purpose. Which of the statement/s below is/are always true based on this computed value for r?
I. The strength of the linear correlation between the petal length and sepal width in Iris setosa is extremely strong.
II. The strength of the linear correlation between these two variables is negligible.
III. The strength of the linear association between these two variables is positive.
IV. The strength of the linear association between these two variables is negative.

6.
A scientist observed that for a certain plant species under certain conditions, the coefficient of linear correlation between the ambient carbon dioxide concentration (in mL/L) and rate of carbon dioxide uptake (in μmol/m²/s) is equal to 0.56. Which of the following best describes the linear association between these two variables of interest?

7.
A taxonomist obtained a sample of a certain species of the iris (Iris virginica). The correlation coefficient between the sepal width and petal length of the flowers in his sample is r = 0.40. The strength of the linear correlation between these two variables is _____.

8.
A senior high school student conducted a minisurvey to determine if the desire to join a basketball varsity team is associated with height among the male members of his peers. The scale for measuring desire that John used in his minisurvey assigns more positive ratings to stronger desires. He obtained a coefficient of linear correlation of r = 0.96. Which of the following best qualifies this association?

9.
In a recent study, a group of medical researchers reported a correlation coefficient of r = 0.75 between percent body fat (%BF) and body mass index (BMI). Based on this value of r, which of the following best qualifies the strength of this association?

10.
To study how Indomethacin is used by the human body, a physiologist measured the Indomethacin concentration every hour for eleven hours in a certain human subject. The coefficient of correlation between these two variables that she obtained based on the data she collected is r = 0.65. What can be said about the strength of the linear correlation between these two variables?

11.
A medical researcher noted that the coefficient of correlation between the dose levels of Vitamin C (from ascorbic acid) and lengths of toothgrowth factors among rats is r = 0.89. Describe the strength of this association.

12.
John is interested in the association between the height and weight of adult males in his country. Using a sample from reliable census data, he obtained an estimate of r = 0.85. Which of the following best qualifies this linear association?

13.
The coefficient of linear correlation between logarithm (base 10) of the revenue passenger miles and integer year from 1937 to 1960 in the US is r = 0.98. This association is said to be _____.

14.
Find from among the following choices, the best description of the strength of the linear correlation between the petal length and sepal length of a certain iris plant species (Iris setosa) if r = 0.23.

15.
A pathologist is testing the effect of a very strong antiseptic on a certain strain of bacterium. He noted that the coefficient of linear correlation between the population size of the bacteria measured at selected times (in sec) with the time equals r = 0.41. Based on this value for r, which of the statement/s below is/are always true?
I. The strength of the linear correlation between the number of virus present and time is extremely strong.
II. The strength of the linear correlation between these two variables is weak or low.
III. The strength of the linear association between these two variables is negative.
IV. The strength of the linear association between these two variables is positive.

16.
A financial analyst obtained the coefficient of linear correlation between the revenue passenger miles and integer year from 1937 to 1960 in the US and obtained r = 0.95. Which of the following best describes this association?

17.
The coefficient of linear correlation between integer year and the number of telephones in the world based on a certain data set covering the years 19511961 is r = 0.96. Which of the following describes this correlation?

18.
For a dataset gathered to study radioactive decay, a nuclear scientist noted that the coefficient of correlation between the amount of the substance remaining at time {eq}x {/eq} and time {eq}x {/eq} is r = 0.005. Choose from among the following the statements that is/are always true based on this computed value of r.
I. The strength of the linear correlation between the amount of substance remaining and time is extremely strong.
II. The strength of the linear correlation between these two variables is negligible.
III. The strength of the association between these two variables is neither negative nor positive.

19.
The coefficient of correlation between the previous year's monthly sales and this year's monthly sales of a certain company is reported as r = 0.65. The strength of this association may be described as a _____.

20.
After a patient has taken some antibiotics, the computed coefficient of linear correlation between the logarithm (base 10) of the population size of a certain pathogen at certain selected time points (in sec) and time equals r = 0.97. Based on this value for r, which of the statement/s below is/are always true?
I. The strength of the association between the logarithm (base 10) of the number of this pathogen present at any given time and time is weak or low.
II. The strength of the linear correlation between these two variables is weak or low.
III. The strength of the linear association between these two variables is very strong.
IV. The strength of the linear association between these two variables is very weak.

21.
A laboratory physics student is studying the relationship between the amount of current passing through a resistor and the amount of the resistance in the resistor, when the voltage drop across the resistor is kept constant. He obtained a number of measurement pairs for these two quantities of interest, then computed the correlation coefficient between the amount of current and the amount of resistance. He obtained a value of r = 0.65. Which of the following is/are always true statements based on this computed value of r?
I. The strength of the association between the current passing through the resistor and the resistance of the resistor is low.
II. The strength of the linear correlation between these two variables is moderately strong.
III. The strength of the linear association between these two variables is negative.
IV. The strength of the linear association between these two variables is positive.

22.
A taxonomist looking into the association between the sepal width and sepal length of the Iris setosa flower computed a correlation coefficient of r = 0.74 from a sample. The strength of this linear correlation is _____.

23.
A financial analyst computed the coefficient of linear correlation between a company's monthly sales during the first five years of the last decade with those of the last five years of the said decade and obtained r = 0.81. Which of the following gives the best description of the strength of this linear association?

24.
In a certain chemical plant that produces nitric acid from ammonia, the coefficient of linear correlation between an index of the concentration of the circulating acid produced and an index of the amount of ammonia that is wasted is reported as r = 0.40. Which of the following best describes this linear association?

25.
For the purpose of evaluating the water quality at a certain location, a researcher gathered data to relate the biochemical oxygen demand (BOD) and the time of day. The estimate of the coefficient of correlation between these two variables based on the data is r = 0.80. Which of the following best describes the association?

26.
A data analyst computed the coefficient of linear correlation between a company's firstquarter sales in the years 19611970 to its firstquarter sales 30 years later, i.e., from 19912000, and obtained r = 0.20. Which of the following best describes the strength of this association?

27.
A molecular biologist studying the growth rate of a certain species of virus computed the correlation coefficient between the number of viruses present inside a particular cell at different time points and the time. The value she obtained is r = 0.015. Based on this value for r, which of the statement/s below is/are always true?
I. The strength of the linear correlation between the number of virus present in a cell at any given time and time is extremely strong.
II. The strength of the linear correlation between these two variables is negligible.
III. The strength of the linear association between these two variables is positive.

28.
A biochemist noted that if a certain plant species from Quebec were chilled overnight, then the coefficient of linear correlation between the ambient carbon dioxide concentration (in mL/L) and rate of carbon dioxide uptake (in μmol/m²/s) is equal to 0.74. This association between the two variables of interest is a _____.

29.
A recent study reported a correlation coefficient of r = 0.75 between percent body fat (%BF) and body mass index (BMI). Find the best description of this association from among the given choices.

30.
A zoologist looking into the relationship of time of day and body temperature among beavers computed a correlation coefficient of r = 0.37 from a dataset that he gathered. Describe the strength of the linear correlation between these two variables based on this dataset.