Answer:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29)
And we can find this probability with the following difference:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29%3D%20P%28Z%3C1.4%29-%20P%28Z%3C0.7%29)
We can use the following commands on the ti 84
2nd>VARS>DISTR
And then we look for normalcdf and we input this:
normalcdf(0.7,1.4,0,1)
The other possible code would be:
normalcdf(-1000,1,4,0,1)-normalcdf(-1000,0.7,0,1)
And we got:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29%3D0.161)
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
For this case we want to find this probability:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29)
And we can find this probability with the following difference:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29%3D%20P%28Z%3C1.4%29-%20P%28Z%3C0.7%29)
We can use the following commands on the ti 84
2nd>VARS>DISTR
And then we look for normalcdf and we input this:
normalcdf(0.7,1.4,0,1)
The other possible code would be:
normalcdf(-1000,1,4,0,1)-normalcdf(-1000,0.7,0,1)
And we got:
![P(0.7](https://tex.z-dn.net/?f=P%280.7%3CZ%3C1.4%29%3D0.161)