Answer:
![z =(26-25)/((3)/(√(50)))= 2.357](https://img.qammunity.org/2021/formulas/mathematics/college/qdvatt2k3ek9u4uq4h0dcnn0ku17rkuw07.png)
And we can find the probability using the normal distribution table and we got:
![P(z<2.357) =0.9908](https://img.qammunity.org/2021/formulas/mathematics/college/k22x99qqfgwx1ko6bfdrk75qvppt60f9re.png)
Explanation:
Let X the random variable of interest and we can find the parameters:
![\mu =25, \sigma= 3](https://img.qammunity.org/2021/formulas/mathematics/college/hmce0eub8c7kxu4kyseqbnb9mu63lfo3bs.png)
And for this case we select a sample size n =50. And since the sample size is higher than 30 we can use the central limit theorem and the distribution for the sample mean would be given by:
![\bar X \sim N(\mu, (\sigma)/(√(n)))](https://img.qammunity.org/2021/formulas/mathematics/college/4bvte95qymxyikwf6tc010pimabbzegclr.png)
We want to find the following probability:
![P(\bar X <26)](https://img.qammunity.org/2021/formulas/mathematics/college/c9lbz3181ys3qkl0cw58drs5gmilj1x38e.png)
And we can use the z score formula given by:
![z =(\bar X -\mu)/((\sigma)/(√(n)))](https://img.qammunity.org/2021/formulas/mathematics/college/ec25opz0iskboyd0wl5m2t1226afp7xia9.png)
And replacing we got:
![z =(26-25)/((3)/(√(50)))= 2.357](https://img.qammunity.org/2021/formulas/mathematics/college/qdvatt2k3ek9u4uq4h0dcnn0ku17rkuw07.png)
And we can find the probability using the normal distribution table and we got:
![P(z<2.357) =0.9908](https://img.qammunity.org/2021/formulas/mathematics/college/k22x99qqfgwx1ko6bfdrk75qvppt60f9re.png)