Application of Normal Distribution: We have a dataset related to health sciences, specifically the Body Mass Index $($BMI$)$ of $50$ patients. Here$$s a small snippet of what the data might look like: ID BMI ID BMI ID BMI ID BMI ID BMI $122\mathrm{.}51124\mathrm{.}82124\mathrm{.}43123\mathrm{.}24122\mathrm{.}9225\mathrm{.}31225\mathrm{.}12225\mathrm{.}83224\mathrm{.}24223\mathrm{.}7323\mathrm{.}11323\mathrm{.}62322\mathrm{.}73325\mathrm{.}44324\mathrm{.}3424\mathrm{.}61424\mathrm{.}32423\mathrm{.}334234425\mathrm{.}1526\mathrm{.}21525\mathrm{.}72524\mathrm{.}735244522\mathrm{.}8623\mathrm{.}71622\mathrm{.}826253625\mathrm{.}54623\mathrm{.}4724\mathrm{.}11723\mathrm{.}52723\mathrm{.}93722\mathrm{.}44724\mathrm{.}4825\mathrm{.}61824\mathrm{.}92824\mathrm{.}53823\mathrm{.}14825\mathrm{.}2922\mathrm{.}91925\mathrm{.}22925\mathrm{.}93924\mathrm{.}14922\mathrm{.}71023\mathrm{.}42023\mathrm{.}83022\mathrm{.}64025\mathrm{.}35024\mathrm{.}1$ Using statistical software $($like R$,$ Python, SPSS$,$ etc.$),$ plot the histogram of the data. Does it look like a normal distribution? Explain. $3.$ Descriptive Statistics: Calculate the mean, median, mode, standard deviation, and variance of the dataset. Plot the data along with its mean and standard deviation on a graph. $4.$ Normality Tests: Conduct a normality test $($e$.$g$.,$ Shapiro$-$Wilk test, Kolmogorov$-$Smirnov test, etc.$)$ on the dataset. Interpret the results. $5.$ Confidence Intervals: Calculate the $95\%$ confidence interval for the mean of the dataset using the concept of standard error. $6.$ Z$-$Scores: Choose a data point from the dataset and calculate its Z$-$score. Interpret the Z$-$score in the context of the dataset.