Question

A regression was run to determine if there is a relationship
between hours of TV watched per day (x) and number of situps a
person can do (y).

The results of the regression were:

y=ax+b a=-1.276 b=24.302 r^{2}=0.779689 r=-0.883

Use this to predict the number of situps a person who watches 3
hours of TV can do (to one decimal place)

Answer #1

A regression was run to determine if there is a relationship
between hours of TV watched per day (x) and number of situps a
person can do (y).
The results of the regression were:
y=ax+b
a=-0.623
b=37.26
r2=0.386884
r=-0.622
Use this to predict the number of situps a person who watches 11.5
hours of TV can do (to one decimal place)

1. A regression analysis was performed to determine if there is
a relationship between hours of TV watched per day (xx) and number
of sit ups a person can do (yy). The results of the regression
were:
y=ax+b
a=-1.072
b=31.456
r2=0.859329
r=-0.927
Use this to predict the number of sit ups a person who watches 8
hours of TV can do, and please round your answer to a whole
number.
2.
The table below shows the number of state-registered automatic...

19
A regression was run to determine if there is a relationship
between hours of TV watched per day (x) and number of situps a
person can do (y).
The results of the regression were:
y=ax+b
a=-1.082
b=36.749
r2=0.6889
r=-0.83
Use this to predict the number of situps a person who watches 7
hours of TV can do (to one decimal place)
18
The table below shows the number of state-registered automatic
weapons and the murder rate for several Northwestern...

1. You want to obtain a sample to estimate a population
proportion. At this point in time, you have no reasonable estimate
for the population proportion. Your would like to be 99.9%
confident that you estimate is within 4% of the true population
proportion. How large of a sample size is required? n =
2. A regression analysis was performed to determine if there is
a relationship between hours of TV watched per day (xx) and number
of sit ups...

A regression was run to determine if there is a relationship
between the happiness index (y) and life expectancy in years of a
given country (x).
The results of the regression were:
y=a+bx
a=-1.921
b=0.058
r2=0.753424
r=0.868
(a) Write the equation of the Least Squares Regression line of the
form
y= + x
(b) If a country increases its life expectancy, the happiness index
will
increase
decrease
(c) If the life expectancy is increased by 3 years in a certain...

A regression was run to determine if there is a relationship
between the happiness index (y) and life expectancy in years of a
given country (x).
The results of the regression were:
y=a+bx
a=0.331
b=0.11
r2=0.405769
r=0.637
(a) Write the equation of the Least Squares Regression line of the
form
y= + x
(b) If a country increases its life expectancy, the happiness index
will
increase
decrease
(c) If the life expectancy is increased by 1.5 years in a certain...

A regression was run to determine if there is a relationship
between the happiness index (y) and life expectancy in years of a
given country (x).
The results of the regression were:
y=a+bx
a=0.13
b=0.198
r2=0.436921
r=0.661
(a) Write the equation of the Least Squares Regression line of the
form
y= + x
(b) If a country increases its life expectancy, the happiness index
will
decrease
increase
(c) If the life expectancy is increased by 2.5 years in a certain...

1. A nutritionist is looking at the connection between hours of
TV watched and choice of sugary snacks in children identified as at
risk for obesity. He asks children to document the number of hours
of TV they watch and the number of sugary snacks they eat each day
as shown in the first three columns of the following table.
Child
Hours of TV watched (X)
Number of sugary snacks eaten (Y)
A
3
3
B
1
3
C
2...

10. In Exercise 6, we examined the relationship between years of
education and hours of television watched per day. We saw that as
education increases, hours of television viewing decreases. The
number of children a family has could also affect how much
television is viewed per day. Having children may lead to more
shared and supervised viewing and thus increases the number of
viewing hours. The following SPSS output displays the relationship
between television viewing (measured in hours per day)...

The number of hours 6 students watched television during the
weekend and the scores of each students who took a test the
following Monday are tabulated below.
Note: X= hours watched, Y=test score
a) find the prediction equation
b) predict the test score for 2.5 hours of TV watching.
0-93
1-86
2-82
3-74
4-84
5-72

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