how to calculate 95% confidence interval in matlab

You can calculate the 95% confidence interval in Matlab by using the t-distribution and the sample statistics. The following code provides an example of how to do this:

main.m
% Define the sample data
data = [1 3 2 5 4 7 6 8 10 9];

% Calculate the sample mean and standard deviation
sample_mean = mean(data);
sample_stdev = std(data);

% Define the alpha value and degrees of freedom
alpha = 0.05;
dof = length(data) - 1;

% Calculate the t-value and margin of error
t_value = abs(tinv(alpha/2,dof));
margin_of_error = t_value * (sample_stdev / sqrt(length(data)));

% Calculate the confidence interval
lower = sample_mean - margin_of_error;
upper = sample_mean + margin_of_error;
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In this example, we first define the sample data as a 1x10 array. Then, we calculate the sample mean and standard deviation using the mean() and std() functions, respectively.

Next, we define the desired alpha value (0.05 for a 95% confidence interval) and the degrees of freedom (one less than the sample size). We then use the tinv() function to calculate the t-value for the specified alpha level and degrees of freedom.

Using the t-value and sample statistics, we calculate the margin of error. Finally, we calculate the lower and upper bounds of the confidence interval by subtracting and adding the margin of error to the sample mean, respectively.

After running this code, the lower and upper variables will contain the lower and upper bounds of the 95% confidence interval, respectively.