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erastova [34]
3 years ago
12

A bank is experimenting with programs to direct bill companies for commercial loans. They are particularly interested in the num

ber of errors of a billing program. To examine a particular program, a simulation of 1000 typical loans is run through the program. The simulation yielded a mean of 4.6 errors with a standard deviation of 0.5. Consturct a 95% confidence interval on the true mean error rate.
Mathematics
2 answers:
larisa [96]3 years ago
8 0

Answer:

95% confidence interval on the true mean error rate = [4.57 , 4.63] .

Step-by-step explanation:

We are given that to examine a particular program, a simulation of 1000 typical loans is run through the program.                                                         The simulation yielded a Mean,Xbar = 4.6 errors with a Standard deviation,s = 0.5.

Since, here we know nothing about population standard deviation so we will use t statistics quantity here i.e.;

                       \frac{Xbar-\mu}{\frac{s}{\sqrt{n} } } ~ t_n_-_1  where, Xbar = sample mean

                                                              s    = sample standard deviation

                                                              n  = sample size(no. of simulations)

                                                              \mu = population mean or true mean

So, 95% confidence interval on the true mean error rate is given by;

P(-1.96 < t_9_9_9 < 1.96) = 0.95 {because at 5% significance level t table gives

                                                  value close to 1.96}

P(-1.96 < \frac{Xbar-\mu}{\frac{s}{\sqrt{n} } }  < 1.96) = 0.95

P(-1.96 * \frac{s}{\sqrt{n} } < Xbar - \mu < 1.96 * \frac{s}{\sqrt{n} } ) = 0.95

P(-Xbar - 1.96 * \frac{s}{\sqrt{n} } < -\mu < Xbar - 1.96 * \frac{s}{\sqrt{n} } ) = 0.95

P( Xbar - 1.96 * \frac{s}{\sqrt{n} } < \mu < Xbar + 1.96 * \frac{s}{\sqrt{n} } ) = 0.95

95% Confidence interval for \mu = [Xbar - 1.96 * \frac{s}{\sqrt{n} } , Xbar + 1.96 * \frac{s}{\sqrt{n} } ]

                                                  = [4.6 - 1.96*\frac{0.5}{\sqrt{1000} } , 4.6 + 1.96*\frac{0.5}{\sqrt{1000} } ]

                                                  = [4.57 , 4.63]

Therefore, 95% confidence interval on the true mean error rate is        [4.57 , 4.63] .

Evgesh-ka [11]3 years ago
7 0

Answer:

The 95% confidence interval for true mean error is (4.57, 4.63).

Step-by-step explanation:

Let <em>X</em> = the number of errors of a billing program.

According to the Central limit theorem if a large sample (<em>n</em> > 30) is drawn from an unknown population then the sampling distribution of the sample mean will follow a Normal distribution with mean (\mu_{\bar x}=\mu) and standard deviation      (\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}).

The sample size of the loans is, <em>n</em> = 1000.

The mean is, {\bar x}=4.6.

The standard deviation is,  \sigma_{\bar x}=\frac{0.50}{\sqrt{1000}}=0.016

The confidence interval for mean is:

CI=\bar x\pm z_{\alpha /2}\times \sigma_{\bar x}

The critical value of <em>z</em> for 95% confidence interval is:

z_{\alpha /2}=z_{0.05/2}=z_{0.025}=1.96

**Use the <em>z</em>-table for critical values.

Compute the 95% confidence interval for true mean error as follows:

CI=\bar x\pm z_{\alpha /2}\times \sigma_{\bar x}\\=4.6\pm1.96\times0.016\\=4.6\pm0.03136\\=(4.56864, 4.63136)\\\approx(4.57, 4.63)

Thus, the 95% confidence interval for true mean error is (4.57, 4.63).

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