ection 1: IntroductionIn this section, tell me about some topic you’re interested in. You can talk about how you firstbecame interested, how long you’ve been following, what you love about it, etc. Try to makeme, as the person reading your project, interested in it as well.Next, list a few questions related to the topic that could be answered by way of statistics. Thereshould be at least one question of the following types: a question concerning qualitative data, aquestion concerning quantitative data, a question concerning the relation between twoquantitative variables, and a question that can be answered by way of a hypothesis test.Summary: This section should have...●A few paragraphs introducing me to the topic.●A question concerning qualitative data.●A question concerning quantitative data.●A question concerning the relation between two quantitative variables.●A question that can be answered with a hypothesis test.Section 2: Qualitative dataGather some data that could answer your question concerning qualitative data. You shouldhave a minimum of 15 observations. Tell me what population you are sampling from, what theindividuals are, how you will sample from the population, and what variable you are collectingfrom the individuals. Mention any possible biases that may contaminate the data. I want to seethat you are mindful of avoiding biases in how you collect the sample data.After describing how the data was collected, give a summary of the data. Since this data iscategorical, a frequency table showing how often each category was observed is appropriate,along with a bar chart or a pie chart.After giving a summary, calculate a confidence interval. Pick some category or categories that,for the purpose of your question, you would consider a “success”. Calculate a 95% confidenceinterval to estimate the proportion of successes.Conclude the section by discussing your results. Are they in line with what you expected, or areyou surprised? Do you have any explanation as to why the categories break down like they do?I’m not necessarily looking for answers to these specific questions, but show me that you’rethinking about what the data might mean.Summary: This section should have...●A minimum of 15 observations of a categorical variable.●Descriptions of the target population, individuals, and the variable being collected.●A description of how the data was collected, and a brief discussion of any possiblebiases.●A numerical summary with a frequency table. There should be a column with relativefrequencies (percents).●A visual summary. Either a bar chart or a pie chart.●Define some category or group of categories as a success, and calculate a 95%confidence interval to estimate the proportion of successes.Section 3: Quantitative dataGather some data that could answer your question concerning quantitative data. You shouldhave a minimum of 15 observations. Again, describe the population, the individuals, thevariable being collected, how you collected the data, and show that you are being careful aboutobtaining a representative sample.List your entire data set, then give some numerical and graphical summaries of the data. Listthe mean, median, standard deviation, 5-number summary, and interquartile range. Create anddisplay a histogram and a boxplot. Create a 95% confidence interval for the mean of the data.Conclude this section by discussing your results. Is the data skewed? If so, in what direction,and why do you have a longer tail in that direction? Are there any outliers in your data? If so,can they be explained? Comment on any other insights you have as well.Summary: This section should have...●A minimum of 15 observations of a quantitative variable.●Descriptions of the target population, individuals, and the variable being collected.●A description of how the data was collected, and a brief discussion of any possiblebiases.●Numerical summaries of the data including the mean, median, standard deviation,5-number summary, and interquartile range.●Two visual summaries, a histogram and a boxplot.●Use the 1.5*IQR rule to check for any outliers.●A brief discussion of any peculiarities in the data, including skew, outliers, explanationsfor each, etc.●A confidence interval for the mean of the dataSection 4: Linear RegressionGather some data that could answer your question concerning the relationship between twoquantitative variables. You should have a minimum of 15 observations of each variable.Describe the population, the individuals, the two variables being collected, and the samplingmethod. If you are clever, you could reuse the data from section 3 as the X (or Y) variable, andtake observations of a different variable from the same individuals as your Y (or X) variable.Calculate and report the coefficient of correlation. Does there appear to be a strong, medium,or weak relationship between the variables? Is the correlation positive or negative? Make ascatter plot of the data. How well does a straight line appear to fit the data? If the relationshipis not linear, what kind of relationship (if any) does it appear to have? Further discuss any otherinteresting aspects of the data you see.Summary: This section should have...●A minimum of 15 pairs of observations.●Descriptions of the target population, individuals, the variables being collected, and thesampling method.●The correlation between the variables, along with an interpretation. For example, acorrelation might be a weak positive correlation, or a strong negative correlation.●A scatter plot of the data, with the least squares line displayed.●Use the least squares line to make a prediction at an X value of your choice.●Discuss any peculiarities of the data. Is the relationship primarily linear, or is there acurve? Are there any outliers?Section 5: Hypothesis testConsider your question that could be answered via one of the 5 kinds of hypothesis tests we’vestudied. Before you collect any data, go ahead and make a guess about what the value of theparameter is. Forming a hypothesis after observing the data is cheating!Once you’ve made your guess, go ahead and collect some data that could confirm or refuteyour hypothesis. If you are clever, you could set it up so you can reuse some of the data from aprevious section. For example, if you are doing a two-sample independent-samples test aboutthe difference of means, you could use your data from Section 3 as one of the samples. Thatway, you would only need to collect one additional sample.Describe the target population, individuals, the variable(s) being collected, and the samplingmethod. Perform the hypothesis test at a 95% confidence level and report your conclusion.Discuss whether your guess was correct.