Base on 3 picture in the attachment. Answer the following question:

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a, Find the sample size (n) for your dataset.

b, Find the counts for your categorical variable.

c, Graph a bar plot with the counts for your categorical variable.

d, Define the "success" (outcome you are interested in)for your categorical variable.

e, Identify your parameter of interest(in context) for this dataset.

f, Identifythe numberof successes (x) for your data.

g, Identify your point estimate in both words and numbers.

h, Verify the conditions for applying the CLT (Central Limit Theorem): independence (Is it a random sample?) and sample size (Are there at least 10 successes and 10 failures?).For independence, check any information on your data set with the "?yourdatasetname" R command. If the conditions are not met or the information is not provided to make this decision, note the possible issues but proceed with finding the confidence interval.

i, Calculate the98% Confidence Interval for your parameter of interest using the sample proportion of successes from the dataset.

j, State the correct interpretation of the confidence interval in wordsin the context of the problem.

> library (openintro) Loading required package: airports Loading required package: cherryblossom Loading required package: usdata Warning message: package 'openintro' was built under R version 4.0.4 data ( ) ?smoking starting httpd help server . . . done > head (smoking) # A tibble: 6 x 12 gender age marital status highest qualifi~ nationality ethnicity 1 Male 38 Divorced No Qualification British White 2 Female 42 Single No Qualification British White Male 40 Married Degree English White 4 Female 40 Married Degree English White 5 Female 39 Married GCSE/0 Level British White Female 37 Married GCSE/O Level British White # . .. with 6 more variables: gross_income , region , smoke , amt weekends , amt_weekdays , type 3 nn [1] 1691 > counts prop. test (x=1270, n, conf . level=0. 98) 1-sample proportions test with continuity correction data: 1270 out of n, null probability 0.5 X-squared = 425.25, df = 1, p-value