Step 1.
Prepare for proposal-Made by Anurag
You will document your preparation in developing the project proposal.
This includes:
1. Which client/dataset did you select and why?
Ans- I chooses sports star data with athletes event and noc region table
because I am very interested in sports, I will love to work on and gather
what can we find from the data.
2. Describe the steps you took to import and clean the data.
Ans- I imported the data at two places first one is in databricks and
second one is in power bi.
1. First I removed the dublicate form the Id column .It will remove all
the dublicate data from the table .
2. I checked all the data type of the columns . corrected it .
3. I replaced all the missing value with null.
4. I replaced all the error caused by the data type correction with
null.
5. I converted the year column into date.
3. Perform initial exploration of data and provide some screenshots or
display some stats of the data you are looking at.
Ans-
4. Create an ERD or proposed ERD to show the relationships of the data
you are exploring.
Ans-
Step-2. Develop Project proposal-
Description
Write a 5-6 sentence paragraph describing your project; include who
might be interested to learn about your findings. Who might be your
audien
Ans- This data is related to sports, It a table contain data of players
related to different sport, how they performed in a event how many
medals the y won and when. The list of interested people and probable
audience will be—
1. Sports Organizations and Teams: Professional sports teams, sports clubs,
or sports federations may be interested in understanding trends in player
demographics (age, height), performance (medals won), and participation in
different sports. They could use this analysis to inform recruitment
strategies, training programs, or talent scouting efforts.
2. Coaches and Trainers: Coaches and trainers at various levels (youth,
amateur, professional) may benefit from insights into the characteristics of
successful athletes, such as the relationship between age, height, and medal
achievements. They could use this information to tailor training programs
and identify potential areas for improvement.
3. Sports Analysts and Journalists: Analysts, journalists, and sports
commentators may be interested in your analysis to uncover interesting
trends or stories within the sports world. They could use your findings to
create compelling narratives, articles, or reports for sports media outlets or
publications.
4. Sports Fans and Enthusiasts: Fans of different sports, including casual
viewers and dedicated enthusiasts, might find your analysis intriguing. They
could be interested in learning more about the demographics of athletes in
their favorite sports, notable achievements, or trends over time.
5. Sports Researchers and Academics: Researchers, academics, and
students in sports science, sports management, or related fields could use
your analysis as a basis for further study or academic research. Your findings
could contribute to a deeper understanding of athlete characteristics and
performance in different sports.
6. Sponsors and Advertisers: Companies or brands that sponsor sports
events, athletes, or sports-related products may be interested in your
analysis to identify potential sponsorship opportunities or target specific
demographics of athletes and sports fans.
Questions
Create 2-3 questions that you want to answer with the data:-
What are the age and height distributions of successful athletes in our
sport?
Which sports are attracting the most talented athletes based on medal
achievements?
How does the age of athletes correlate with their performance and
medal success?
Are there any emerging trends in athlete demographics or
performance that we should be aware of?
How can we use this analysis to optimize our recruitment strategies or
identify potential areas for talent development?
Hypothesis
What are your initial hypotheses about the data?
Ans-
1. Age and Performance: Hypothesize that there is a relationship between
the age of athletes and their performance in sports. For example, you could
investigate whether athletes tend to peak at a certain age or if younger or
older athletes have an advantage in specific sports.
2. Height and Success: Explore whether there is a correlation between the
height of athletes and their success in different sports. You could examine
whether taller athletes tend to perform better in certain sports that require
physical attributes like basketball or volleyball.
3. Sport Participation Trends: Hypothesize about trends in sport
participation over time. For instance, you could investigate whether certain
sports have grown or declined in popularity over the years and explore
potential factors driving these trends.
4. Medal Success and Country Wealth: Investigate whether there is a
relationship between a country's economic wealth and its success in winning
medals at international sporting events like the Olympics. You could examine
whether wealthier countries tend to win more medals overall or if there are
other factors at play.
Approach
Describe in 5-6 sentences what approach you are going to take in order
to prove (or disprove) your hypotheses. Think about the following in
your answer: -
Ans-
Approach to Hypothesis Testing
1. Identify Key Features: Determine relevant columns such as "Age",
"Height", "Medal", "Sport", and "Year" based on the hypotheses being tested.
2. Exploratory Data Analysis (EDA): Conduct EDA to visualize data
distributions and identify patterns using scatter plots, histograms, and box
plots.
3. Assess Relationships: Calculate correlation coefficients to quantify
relationships between variables (e.g., age and medal count).
4. Statistical Testing: Use appropriate statistical tests (e.g., t-tests, chi-
square tests, regression analysis) to evaluate hypotheses based on data
characteristics and research questions.
5. Interpretation and Conclusion: Interpret results of analysis to determine
if hypotheses are supported by the data, providing clear conclusions and
implications.
