Using the t-distribution, it is found that the most appropriate conclusion for the hypotesis test is given by:

Phone use did not change.

What are the hypothesis tested?

At the null hypothesis, we test if the mean has not changed, that is:

[tex]H_0: \mu = 0[/tex]

At the alternative hypothesis, we test if it has changed, that is:

[tex]H_1: \mu \neq 0[/tex].

What is the test statistic?

The test statistic is given by:

[tex]t = \frac{\overline{x} - \mu}{\frac{s}{\sqrt{n}}}[/tex]

The parameters are:

- [tex]\overline{x}[/tex] is the sample mean.

- [tex]\mu[/tex] is the value tested at the null hypothesis.

- s is the standard deviation of the sample.

- n is the sample size.

In this problem, the values of those parameters are as follows:

[tex]\overline{x} = -0.2, \mu = 0, s = 9.1, s = 200[/tex]

Hence, the test statistic is given by:

[tex]t = \frac{\overline{x} - \mu}{\frac{s}{\sqrt{n}}}[/tex]

[tex]t = \frac{-0.2 - 0}{\frac{9.1}{\sqrt{200}}}[/tex]

t = 0.31.

What is the conclusion?

Considering a two-tailed test, as we are testing if the mean is different of a value, with a standard significance level of 0.05 and 200 - 1 = 199 df, the critical value is of [tex]|t^{\ast}| = 1.972[/tex].

Since the absolute value of the test statistic is less than the critical value, we do not reject the null hypothesis and the conclusion is:

Phone use did not change.

More can be learned about the t-distribution at