Introduction

This Dataset is wide with 25 variables and 5591 observations. There are 5 different (Breastfeeding, Sugary Drinks, Physical Activity, Fruits and Vegetables and Televison watching), 5 topics and 27 different questions. Each question should have their own column based on the class they belong to since some values are listed as percentages, averages and “number of”. A table is created for each class. Only 2 tables will be focused on in this dataset for this project. For more information, visit HeathData.gov

Full Data

Subset

Some of the columns were removed as they are not relevant to the analysis.

Areas Covered

Breast Feeding

Please note no data were collected for the Le Leche League until 2011.

Live Birth at Baby Friendly Facilities Summary (%)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  0.000   0.000   5.500   9.576  13.000  99.800       1 

Here the distribution is skewed to the right. The peak of the histogram hits where as stated in the summary above at an average of 9%. Not every child will be born at a “baby-friendly” facility. Usually when someone is about to give birth (unplanned), they’re taken to the nearest hospital/clinic unless the birth is as expected. Also, there is a possibility of the state or city being small and there is one or two clinics around. In this case, the percentage will be higher of having babies born at one of those “baby-friendly” facilities.

This line graph shows averages among baby facilities over a 10 year span. It displays how much attention was drawn to the awareness of Practice in Infant nutrition and care. As the years increase more peope are becoming more involved and educated about this practce. As we can see, by the end of 2007-2008 most average scores ranged up to about 82 but after 2010 onto 2017 we see the scores increased atleast 17%.

Sugar Drinks

Which State’s secondary schools prevent students from buying soda, fruit or sport drinks from venging machines?

They all seem to indicate NO about not allowing students to buy drinks other than water at school.

Soda Summary

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   2.90   14.93   22.65   24.68   34.38   56.10 

Sports Summary

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   6.70   35.23   43.60   43.94   56.62   73.80 

Accoring to the graphs above, it seems as though more schools allowed kids to drink sports drinks rather than soda or fruit drinks. Graph A is slightly skewed to the right. They both do not show any extreme deviations so they can both come from a normal model. For soda and sugar drinks, the highest counts range between 10% and 25% while sports drinks populate most between 35% and 55%. This is proven via the summary above mentioning the mean and median for this data.

A lot of times fruit or soda drinks have a empty calories and tons of sugar which make kids hyper then they become lethargic. On the other hand, sport drinks are viewed to replenish energy and keeping kids active. Many sport drinks are endorsed by athletes who kids look up to and wishes to emulate. Schools encourage physical fitness among kids hence why majority of them would allow more sport drinks than soda/fruit drinks.

Conclusion

The awareness of educating moms the importance of breast feeding is rising. Secondary schools in every state will continue to allow students to buy drinks other than water from the schools. We can all agree that kids are active with or without sugar.

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Introduction

This dataset was chosen to have an idea of how the apps are used with the Google Play Store. We will discover which types of apps are downloaded the most and which ones are people likely to pay for. We also get a view of how reviews or ratings affect what people download. Find dataset at Kaggle.com for further details.

Here is a view of the dataset.

Subset but cleaned data

Downloads

Games are the most downloaded types of apps with Communication second. It seems as though apps that are usually paid for has the least set of downloads which is understandable. Sometimes, most downloaded apps does not mean that people like them but just wanted to pursue a trial first then maybe delete them.

Content Ratings

Grade	Count	Relative_Frequency	Cummulative_Frequency
Adults only 18+	3	0.0002768	0.0002768
Everyone	8714	0.8039487	0.8042255
Everyone 10+	413	0.0381031	0.8423286
Mature 17+	499	0.0460375	0.8883661
Teen	1208	0.1114494	0.9998155
Unrated	2	0.0001845	1.0000000

80% of the apps are made for Everyone to use.

Most Expensive

Assuming $50 and up is considered expensive then most expensive apps belong in Medical and Lifestyle. People are willing to pay for apps that will benefit them in the long run.

Paid vs Free

Var1	Freq
Free	10039
Paid	800

According to the dataset, 10000+ apps are free which is equvialient to approximately 93% of the apps in Google Play Store. Free apps are more popular among the users and hence they get the most reviews.

There are more downloads with free apps than paid ones. This makes sense because people would rather try out the app first before purchasing the professional version if there is such. Another reason is that developers make more money this way. They create the apps in a way that there are in-app purchases especially in games. It’s a win-win- situation.

Average Ratings

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
  1.000   4.000   4.300   4.192   4.500   5.000    1473 

This histogram is skewed to the lower end. 73% of the ratings scores fall within 4 and 5. This shows people are overall satisfied with majority of the apps in the Google Play Store.

Apps in Categories such as Education, Entertainment and Weather seems to do really well with the fact that their lowest ratings are no lower than 3.

Relationship?

Which explanatory variable affects how much time an app is installed or downloaded: Rating or Reviews?

There is a strong positive correlation between Installs and Reviews. This shows that people down load apps based on the reviews more than they do over the ratings. There are some outliers present in both plots especially in the relationship between Installs and Rating.

Conclusion

What can be concluded from the reports above in the Google Play Store is that, people generally like to know how a product is doing before they invest time into it. Medical anf Finance apps are the apps people would most likely pay for. On the other hand Gaming and Communication are the top categories people download apps and are free for the public.

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Introduction

The data in this section is more a qualitative one. It was used to find out which teams or players had the most wins. Find the table on ESPN website.

Untidy

Tidy

	SUPERBOWL	Player	Position	Team	HIGHLIGHTS
2	I	Bart Starr	QB	Green Bay	Two touchdown passes
3	II	Bart Starr	QB	Green Bay	202 yards passing, 1 TD
4	III	Joe Namath	QB	New York Jets	206 yards passing
5	IV	Len Dawson	QB	Kansas City	142 yards passing, 1 TD
6	V	Chuck Howley	LB	Dallas	Two interceptions, fumble recovery
7	VI	Roger Staubach	QB	Dallas	119 yards passing, 2 TDs

TOP MVP PLAYER

The top player is Tom Brady with 4 wins! 
He won the following Superbowls:
 XXXVI XXXVIII XLIX LI

Positions Winners Played

Position	Position_name
QB	Quaterback
LB	Line Backer
S	Safety
FB	Fullback
RB	Running Back
WR	Wide Receiver
DL	Defense Line
DE	Defensive End
CB	Cornerback
KR	Kick Returner

Which position is best?

Proof that Quaterback player is the best on the teams in football.

Popular Team?

Looks like Dallas, New England and Pittsburgh tied for the top.