A well-known brokerage firm executive claimed that at least 50 % of investors are currently confident of meeting their investment goals. An XYZ Investor Optimism Survey, conducted over a two week period, found that out of 86 randomly selected people, 47 of them said they are confident of meeting their goals. Suppose you are have the following null and alternative hypotheses for a test you are running: Ho: p = 0.5 Ha: p > 0.5 Calculate the test statistic, rounded to 3 decimal places Check Answer

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### Investor Confidence Hypothesis Testing

A well-known brokerage firm executive claimed that at least 50% of investors are currently confident of meeting their investment goals. An XYZ Investor Optimism Survey, conducted over a two-week period, found that out of 86 randomly selected people, 47 of them said they are confident of meeting their goals.

#### Hypothesis Testing
Suppose you have the following null and alternative hypotheses for a test you are running:
- **Null Hypothesis (H₀):** \( p = 0.5 \)
- **Alternative Hypothesis (Hₐ):** \( p > 0.5 \)

#### Calculation of the Test Statistic
To determine whether the proportion of confident investors is significantly greater than 0.5, we calculate the test statistic. The calculation is based on the sample proportion and the population proportion provided in the hypotheses.

Use the formula for the test statistic (z):
\[ z = \frac{\hat{p} - p_0}{\sqrt{\frac{p_0 (1 - p_0)}{n}}} \]

Where:
- \( \hat{p} \) is the sample proportion
- \( p_0 \) is the population proportion under the null hypothesis
- \( n \) is the sample size

Plug in the values:
- \( \hat{p} = \frac{47}{86} \)
- \( p_0 = 0.5 \)
- \( n = 86 \)

The formula now becomes:
\[ z = \frac{\frac{47}{86} - 0.5}{\sqrt{\frac{0.5 (1 - 0.5)}{86}}} \]

Calculate the test statistic, rounded to 3 decimal places:
\[ z =  \]

*(The user is expected to fill in the calculated value.)*

#### Input Area
To complete the test, enter the calculated test statistic in the box provided and click the "Check Answer" button to see if your computation is correct.

```plaintext
z = [__]
```

*Note: The detailed calculations and interpretations are essential to formally conclude the hypothesis testing.*
Transcribed Image Text:### Investor Confidence Hypothesis Testing A well-known brokerage firm executive claimed that at least 50% of investors are currently confident of meeting their investment goals. An XYZ Investor Optimism Survey, conducted over a two-week period, found that out of 86 randomly selected people, 47 of them said they are confident of meeting their goals. #### Hypothesis Testing Suppose you have the following null and alternative hypotheses for a test you are running: - **Null Hypothesis (H₀):** \( p = 0.5 \) - **Alternative Hypothesis (Hₐ):** \( p > 0.5 \) #### Calculation of the Test Statistic To determine whether the proportion of confident investors is significantly greater than 0.5, we calculate the test statistic. The calculation is based on the sample proportion and the population proportion provided in the hypotheses. Use the formula for the test statistic (z): \[ z = \frac{\hat{p} - p_0}{\sqrt{\frac{p_0 (1 - p_0)}{n}}} \] Where: - \( \hat{p} \) is the sample proportion - \( p_0 \) is the population proportion under the null hypothesis - \( n \) is the sample size Plug in the values: - \( \hat{p} = \frac{47}{86} \) - \( p_0 = 0.5 \) - \( n = 86 \) The formula now becomes: \[ z = \frac{\frac{47}{86} - 0.5}{\sqrt{\frac{0.5 (1 - 0.5)}{86}}} \] Calculate the test statistic, rounded to 3 decimal places: \[ z = \] *(The user is expected to fill in the calculated value.)* #### Input Area To complete the test, enter the calculated test statistic in the box provided and click the "Check Answer" button to see if your computation is correct. ```plaintext z = [__] ``` *Note: The detailed calculations and interpretations are essential to formally conclude the hypothesis testing.*
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