10 springs have been tested and have had their spring constant recorded. This data has been provided in a csv file 10.051, 9.5551, 9.806, 9.9991, 10.191, 10.259, 9.8472, 9.4386, 9.4493, 9.5575 1. Using MATLAB, import the data using csvread and determine the sample mean and variance using in built functions is fine)(finished) 2. Determine the 95% confidence interval for the spring constant of the springs finished) x = csvread(“values csv”) m = mean(x); v = var(x); sprintf (“Mean is %f and Variance is %f, m, v) se= squareroot (v)/ squareroot (length(x)); t = tinv ([0.025 0.975], length(x) – 1); Cl = m + t* se; sprintf “Calculated Confidence interval is %f to %f”, Cl(1), Cl(2)) unfinishing are 3 and 4.(clear code please) (clear code please) 3. The spring manufacturer claims that the springs have a spring constant of 10kN/m. Conduct a hypothesis test to see if there is sufficient evidence to suggest that this spring constant is incorrect. Use the comparison between test T_test and t_N, 1, 1 -alpha/2 for your hypothesis test. 4. If the sample mean and variance stayed the same, but there were 50 springs, calculate the new 95% confidence intervals and reconduct a hypothesis test. Explain why the confidence interval changes.