1. Create Dataset with at least 30 observations-What is the decision
Create your own dataset that includes at least 30 observations for four different variables,
i.e. minimum 30 rows, 4 columnsYou have created a copy of the raw data and labeled the
sheet ‘Raw Data’You have renamed the sheet you are working with ‘Analysis.’ The first step
is to add at least one column and transform an existing variable (e.g., from text to a
quantitative variable). You can choose any variable you want to transform. Hint: you should
most likely be using an if() function to complete this step.You have provided descriptive
(summary) statistics for each variable in a new sheet named ‘Descriptive Stats’ – refer back
to the first weeks of class to see what is meant by descriptive statistics. Use your own
judgment on how to best show the data.You have described the distribution of at least one
variable in a sheet named ‘Distribution’ – you should use a histogram and its chart to show
the distribution of the variable. In cell A1, explain why you think the variable has its
distribution. Are there any outliers? How do you know?You have completed a t-test on
comparing two variables in a sheet named ‘t-test’. In a cell of your choice, explain what the
t-test tells you in plain English. The description should be at least 10 sentences. You need to
describe a reason or multiple reasons why that test would make sense. It is ok to make
some assumptions and be creative – in other words, tell a story about the data.You have
completed either a decision making (input/output) model based on the data (using solver,
expected value, or a custom model similar to what we performed in class) OR a regression
and explained the regression in a sheet named ‘regression.’ In a cell of your choice, explain
the input/output model or what the regression tells you in plain English. Again, you need to
describe why you chose this methodology to look at the data. It is ok to make some
assumptions and be creative – in other words, tell a story about the data.You have explained
in a sheet named ‘Discussion’ describing what data is missing that would help make a better
decision. What is the decision you could make from the data set if you could magically snap
your fingers and have the data. What type of statistical test might you run to complete the
analysis with the new data.