You are required to find data sample (see below) and undertake inferential statistical analysis in order to test some hypotheses about the population the sample data comes from. We will allocate on-campus class time to searching for relevant data where you can get tutor feedback on the suitability of your dataset choice in the class. Possible sources of data: Any data we have used on the course or one you find yourself, for example: https://www.kaggle.com/datasets?license=cc https://github.com/awesomedata/awesome-public-datasets https://github.com/fivethirtyeight/data https://opendata.bristol.gov.uk/pages/homepage/ Notes: Make sure the data you are using is open access, in the public domain or has a Creative Commons license and you have at least one hundred records/rows in your dataset. Make sure your dataset includes data that will allow you to divide your respondents into two or more groups, eg: gender, status, education level etc. Make sure your dataset includes variables with data measured on a ratio scale, eg: money, number of purchases, distance etc. What you are required to do... Write a short summary of your data (1000 words 10%) to include the following: Task 1 (20%: 150 words for the overview, the classification table doesn't count for wordcount) Provide a brief overview of your dataset and the type of data you have - this should comprise a short description of the context/background of your data and classify each column of data in a table that lists the column name, description of data and type of data in your dataset. Task 2 (60%: 600 words in total, 200 words per inference) On the basis of your sample data, make three different inferences about the relevant population using the tools and techniques we have covered in the module. For each inference indicate any limitations of your method, assumptions that are required to make your conclusions valid, and interpret the outcome of your analysis within the context of your data set. You should either write out the steps in your calculations or copy/paste from your spreadsheet to show your method for each separate inference. Your data set may not permit all the tests we have covered, so you need to select an appropriate dataset that will allow you to perform three different statistical tests. This is why the dataset selection is vitally important (see above). Task 3 (20%: 250 words for the discussion) Discuss any shortcomings of the dataset you have used and discuss the advantages and limitations of business decision-making methods such as those you have used in your dataset in Task 2 to address real-world managerial situations. This question is from data-driven decision-making module. You will need to select only 1 dataset from the given open links and perform any 3 different tests on the dataset. the testing methods include hypothesis testing, sampling, correlation and regression, and confidence intervals. please use the Excel sheets for the calculations and also provide each step. I would like to request to please answer my question as soon as possible as i have already waited for more than 2 hours now. Thank you.