Question

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 |
1 |

D |
4 |
2 |

E |
5 |
4 |

a. What type of research design is represented in this study (experimental? Non-experimental? Correlational?). Explain your answer

b. What do you think the independent variable is? What is the scale of measurement?

c. What do you think the dependent variable is? What is the scale of measurement?

d. For hours of TV watched, calculate the mean and standard deviation and Z score for each child

e. For number of sugary snacks eaten, calculate the mean and standard deviation and Z score for each child

f. Comparing the Z scores for each child (on TV and snacks), do you notice any trend in the data? Describe

Answer #1

(a) Correlational research design is represented in this study because a nutritionist is looking at the connection between hours of TV watched and choice of sugary snacks in children.

(b) The independent variable is the hours of TV watched and the scale of measurement is ratio.

(c) The dependent variable is the Number of sugary snacks eaten and the scale of measurement is interval.

(d)

Hours of TV watched | Z-score | |

3 | 0 | |

1 | -1.26491 | |

2 | -0.63246 | |

4 | 0.632456 | |

5 | 1.264911 | |

Mean | 3 | |

Standard deviation | 1.581139 |

(e)

Number of sugary snacks eaten | Z-score | |

3 | 0.350823 | |

3 | 0.350823 | |

1 | -1.40329 | |

2 | -0.52623 | |

4 | 1.227881 | |

Mean | 2.6 | |

Standard deviation | 1.140175 |

(f) There is a positive relationship between hours of TV watched and choice of sugary snacks.

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The population mean number of hours a group watched TV was 8.0
with a standard deviation of 2.0. A random sample of 36 individuals
from the group was selected and the number of hours each watched TV
was obtained. Consider the statistic the sample mean number of
hours the studied group of 36 watched TV.
Question 6 options:
123456789
Consider the statistic the sample mean number of hours the
studied group of 36 watched TV. What is the standard deviation...

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
r2=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)

According to the South Dakota Department of Health, the number
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adult men. A recent study showed women spent an average of 30 hours
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hours and is 5.0 hours for the men. What percent...

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chart. Each child is asked to record the number of hours spent each
day watching TV. The average for this sample is M = 4.9 hours. It
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THIS IS AN EPIDEMIOLOGY QUESTION: PLEASE ONLY ANSWER IF
YOU HAVE EPIDEMIOLOGY EXPERIENCE
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Time spent indoors (hours)
3
5
6
9
10
9
8
10
10
12
13
11
16
11
7
8
18
13
12
13
1.Can you calculate z-scores for each of the raw scores above?
If so, please calculate the z-score for a kid who reported spending
8 hours indoors.
2. if you transformed the variable “time spent indoors” from an
X-scale to a z-scale, what would be the new mean of the
distribution? What would be the new standard...

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
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Match each of the research designs below to the
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z Test
Single Sample t-Test
Paired Samples t-Test
Independent Samples t-test
One-way Between-Groups Analysis of
Variance
One-way Within-Subjects Analysis of
Variance
Two-way Analysis of Variance
Correlation
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dependent variable. For example, you want to know if the various
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