Quiz3

The data set is from a case-control study of smoking and Alzheimer’s disease. The data set has two variables of main interest:

• smoking a factor with four levels “None”, “<10”, “10-20”, and “>20” (cigarettes per day)
• disease a factor with three levels “Alzheimer”, “Other dementias”, and “Other diagnoses”.

##                 smoking None <10 10-20 >20
## disease                                   
## Alzheimer                126  15    30  27
## Other dementias           79   8    33  44
## Other diagnoses          104   5    47  20

Q1 Describe the largest group that has Alzheimer. Discuss it by number of cigarettes per day.

This group would be known as the “non-smokers”. If you look at the plot, the largest box clearly the non smokers, which obviously means they do not smoke any cigarettes. ## Q2 Describe one group that has more cases than expected given independence (by chance). Discuss it by number of cigarettes per day.

The specific group that would be entailed to having more cases than expected is the “dementias”; and to my knowledge they smoke over 20 because the blue box shows there are an above-expected amount of cases.

Q3 Does smoking seem to matter in determining Alzheimer? Discuss your reason using the masaic chart above.

Relating back to question one, it seems to me that there is no correlation between smoking and Alzheimers. This is because when yiou look at the chart, most people who are indeed diagnosed with it tend to be non smokers, so if the majority does not smoke, how would smoking be an influence of obtaining it.

Q4 Create correlation plot for RailTrail.

Hint: The RailTrail data set is from the mosaicData package.

##            hightemp lowtemp avgtemp spring summer  fall cloudcover precip
## hightemp       1.00    0.66    0.92  -0.33   0.67 -0.40      -0.10   0.13
## lowtemp        0.66    1.00    0.90  -0.39   0.74 -0.41       0.37   0.37
## avgtemp        0.92    0.90    1.00  -0.39   0.77 -0.44       0.14   0.27
## spring        -0.33   -0.39   -0.39   1.00  -0.74 -0.47      -0.10  -0.25
## summer         0.67    0.74    0.77  -0.74   1.00 -0.24       0.17   0.34
## fall          -0.40   -0.41   -0.44  -0.47  -0.24  1.00      -0.08  -0.09
## cloudcover    -0.10    0.37    0.14  -0.10   0.17 -0.08       1.00   0.37
## precip         0.13    0.37    0.27  -0.25   0.34 -0.09       0.37   1.00
## volume         0.58    0.18    0.43  -0.04   0.23 -0.25      -0.37  -0.23
##            volume
## hightemp     0.58
## lowtemp      0.18
## avgtemp      0.43
## spring      -0.04
## summer       0.23
## fall        -0.25
## cloudcover  -0.37
## precip      -0.23
## volume       1.00

Q5 What variables have positve correlation with the number of trail users (volume)?

summer; high temp; low temp; and average temp.

Q6 What season seems to be most popular for trail users?

Based off the correlation plot, “Summer” seems to be the most popular season for most trail users

Q7 The correlation coefficient between hightemp and cloudcover is quite small. Would you be sure that the two variables are not related at all? Create scatter plot. After examing the scatter plot, would you conclude that the two variables are not related at all?

Hint: Discuss your reason by explaining your scatter plot.

Yes, I would indeed conclude that there is no correlation because the points are everywhere on the plot and there are a ton of outliers.

Q8 Hide the messages, the code and its results on the webpage.

Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.