To calculate the standardized test statistic, we need more information. The formula for the standardized test statistic depends on the type of test you're conducting (e.g., $z$-test or $t$-test) and the data available. Here are the most common cases:

1. For a $z$-test (when population standard deviation is known): $z = \frac{\bar{x} - \mu}{\frac{\sigma}{\sqrt{n}}}$ where:

   • $\bar{x}$ is the sample mean,
   • $\mu$ is the population mean,
   • $\sigma$ is the population standard deviation,
   • $n$ is the sample size.

2. For a $t$-test (when population standard deviation is unknown): $t = \frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}}}$ where:

   • $s$ is the sample standard deviation (since population standard deviation $\sigma$ is unknown).

3. For a proportion $z$-test: $z = \frac{\hat{p} - p}{\sqrt{\frac{p(1 - p)}{n}}}$ where:

   • $\hat{p}$ is the sample proportion,
   • $p$ is the population proportion,
   • $n$ is the sample size.

If you can provide the values for the mean, standard deviation, sample size, or any other relevant information, I can calculate the standardized test statistic for you and round it to two decimal places.

Would you like to provide the values, or do you need further guidance on which formula to use?

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Here are five related questions that may be helpful for you:

1. What is the difference between a $z$-test and a $t$-test?
2. How do you determine whether to use population or sample standard deviation?
3. What is the importance of sample size in hypothesis testing?
4. When would you use a one-tailed test versus a two-tailed test?
5. How does the level of significance ($\alpha$) affect hypothesis testing?

Tip: Always verify whether you know the population standard deviation before choosing between a $z$-test and a $t$-test.