Question

**RESEARCH QUESTION 1:** Are amount of school loan
debt, hours of sleep per night, age, time spent in community
service, and stress related to each other? These variables are in
SPSS as:debt, sleep, age, service, and stress. Each of these
variables was measured so that a **bigger value equals
more** (ex. 1 = no stress, 7 = high stress).

Based on your investigation of how these variables relate to each
other in SPSS, select the variables that are significantly
correlated with **debt** (you may select more than one
variable). Note that significant equals any p value ("sig.") that
is less than .05 (any p value from .000 to .049 is significant; A p
value of .000 in SPSS simply means it is smaller than .001).

hours of sleep per night |

age |

time spent in community service |

stress |

Match the variables with the correct description of how they are correlated. "Significant" for this assignment is p<.05 (less than .05 = anything from 0.000 to .049).

debt x age

[ Choose ]
**These variables are not
significantly correlated**
These variables are significantly, positively
correlated These
variables are significantly, negatively correlated

debt x hours of sleep

[ Choose ]
These variables are not significantly
correlated These
variables are significantly, positively correlated
**These variables are
significantly, negatively correlated**

debt x stress

[ Choose ]
These variables are not significantly
correlated
**These variables are significantly, positively
correlated**
These variables are significantly, negatively
correlated

debt x community service

**These variables are not
significantly correlated**
These variables are significantly, positively
correlated These
variables are significantly, negatively correlated

Select the conclusions we could draw based on the correlations
you found in your analysis (you may select more than one).

Remember, if a finding is not significant, then we do not take the
time to describe how they are related because they are NOT related.
"Significant" for this assignment is p<.05.

People with more debt tend to be more
stressed. |

People with more debt tend to be less stressed. |

Debt and stress are not significantly related. |

People with more debt tend to sleep more. |

People with more debt tend to sleep less. |

Debt and sleep are not significantly related. |

Older people tend to have more debt. |

Younger people tend to have more debt. |

Age and debt are not significantly
related. |

People with more debt tend to give more community service. |

People with more debt tend to give less community service. |

Debt and community service are not significantly
related. |

**RESEARCH QUESTION 2:** Now you wonder what
variables might **predict stress.** You specifically
decide to investigate whether gender, age, and sleep predict
stress.

You run the appropriate analysis and find that the OVERALL linear
combination is

[**note that "significant at the .05 level" means p <
.05**]:

significant at the .05 level. |

not significant at the .05 level. |

Indicate which variables SIGNIFICANTLY (p<.05) predict stress (you may select more than one variable).

gender |

age |

sleep |

None of these variables significantly predict the outcome variable |

Indicate the following conclusions that can be made based on your analysis of the predictors of stress and their significance. Note that significant is when p<.05. You may select more than one option below.

Remember, if a variable is **not** significant,
then we do not make any interpretations beyond: X is not
significantly related to Y.

NONE of these variables are significant predictors of stress. |

For every one hour increase in sleep, we can expect a .33 point increase in stress on the stress scale. |

For every one hour increase in sleep, we can expect a .33 point decrease in stress on the stress scale. |

For every one point increase in stress, we can expect a .308 point increase in sleep. |

For every one point increase in stress, we can expect a .308 point decrease in sleep. |

Sleep and stress are not significantly related. |

Men are significantly more stressed than women. |

Women are significantly more stressed than men. |

Men and women do not significantly differ in stress. |

For every one year increase in age, we can expect a .005 point increase in stress on the stress scale. |

For every one year increase in age, we can expect a .005 point decrease in stress on the stress scale. |

For every one year increase in age, we can expect a .028 point increase in stress on the stress scale. |

For every one year increase in age, we can expect a .028 point decrease in stress on the stress scale. |

Answer #1

This question is incomplete since the dataset for correlation analysis is not provided.

However, reference to internet provides us with the dataset . We downloaded the dataset and ran correlation analysis in excel (data analysis-> correlation) and got a summary of correation between the various factors as mentioned above.

Now i base my responses on the infereces from the summary of correlation analysis above.

a) .From the analysis above we can see that debt is positively and significently related to stress and negetively &significently correlated to Sleep (p value <0.05)

Research Q2

Clearly from the analysis above we see that

1. Stress is correlated negetively to sleep (p val <0.05)

2. Stress is positvely correlated to debt (p val <0.05)

Thus ,

1. We see that the equation is significant (option -1)

2. Sleep is negetively correlated to stress (optino-3)

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Key Terms
----------------------------------------------------------------------------------------------------------------------------
Positive relationship --- Occurs in so far as pairs of
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respective distribution.
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observations tend to occupy dissimilar relative positions in their
respective distribution.
Scatterplot --- a graph containing a cluster of dots
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Person correlation coefficient --- A number between –1
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