Company stock price of which has risen so that over the past ten trading days , it's mean selling price is $ 14.89 . Over the years the mean price of the stock has been 10.43 ( sigma = 5.60 ) you wonder if the mean selling price is over the next ten days to go higher . Should you wait to sell , or should you sell now ?
Find the z-scre
14.98 - 10.43 divided by 5.60
z=.8125
Once the z score is 2 or greater than what happens would be highly unusual. Since the z-score is less than 2, I would say it is possible for the stock to go up.
To determine whether you should wait to sell or sell now, we can use statistical analysis.
Given that the mean selling price over the past ten trading days is $14.89 and the mean price of the stock over the years is $10.43 with a standard deviation of $5.60, we can perform a hypothesis test to see if the mean selling price over the next ten days is expected to be higher.
Here's how you can perform the hypothesis test:
Step 1: Define the null and alternative hypotheses:
- Null Hypothesis (H0): The mean selling price over the next ten days is not significantly higher than the mean price over the years.
- Alternative Hypothesis (Ha): The mean selling price over the next ten days is significantly higher than the mean price over the years.
Step 2: Choose the significance level (alpha):
The significance level, denoted as alpha (α), helps determine the threshold for accepting or rejecting the null hypothesis. Let's assume a commonly used significance level of α = 0.05, which corresponds to a 5% chance of rejecting the null hypothesis when it is true.
Step 3: Conduct the hypothesis test:
To test the hypothesis, we can calculate the test statistic Z using the formula:
Z = (sample mean - population mean) / (population standard deviation / sqrt(sample size))
In this case, the sample mean is $14.89, the population mean is $10.43, the population standard deviation is $5.60, and the sample size is 10.
Step 4: Determine the p-value:
Using the Z score obtained in step 3, we can calculate the p-value associated with it. The p-value represents the probability of obtaining a test statistic as extreme as the one calculated, assuming the null hypothesis is true.
Step 5: Compare the p-value with the significance level:
If the p-value is less than the significance level (α), we reject the null hypothesis. Otherwise, if the p-value is greater than or equal to α, we fail to reject the null hypothesis.
Step 6: Interpret the results:
Based on the outcome of the hypothesis test, you can decide whether to wait to sell or sell now. If the p-value is less than α, it suggests that the mean selling price over the next ten days is significantly higher than the historical mean price, indicating that you should wait to sell. On the other hand, if the p-value is greater than or equal to α, there is not enough evidence to conclude that the mean selling price will be significantly higher, suggesting that selling now might be a reasonable decision.
Performing the calculations and hypothesis test should provide you with a recommendation regarding whether to wait or sell now based on statistical evidence.