In a recent survey, it was stated that Malaysians watch videos on YouTube on average two hours per day. Assume that σ = 2. Using students in UTeM as the sample, conduct a hypothesis test to determine if the average for students at UTeM is lower

Ho: mean = 2

Ha: mean < 2

Once you get UTeM data, insert.

Z = (mean1 - mean2)/standard error (SE) of difference between means

SEdiff = √(SEmean1^2 + SEmean2^2)

SEm = SD/√n

If only one SD is provided, you can use just that to determine SEdiff.

Find table in the back of your statistics text labeled something like "areas under normal distribution" to find the proportion/probability related to the Z score. Is it < your level of significance?

In order to conduct a hypothesis test to determine if the average video-watching time for students at UTeM is lower than the reported average of two hours per day, we need to define our null and alternate hypotheses and select an appropriate significance level.

Step 1: Define the hypotheses
Null hypothesis (H0): The average video-watching time for students at UTeM is equal to two hours per day.
Alternate hypothesis (Ha): The average video-watching time for students at UTeM is lower than two hours per day.

Step 2: Select the significance level
The significance level, denoted as α, determines how confident we want to be in our conclusion. Commonly used values are 0.05 (5%) and 0.01 (1%). For this example, let's use a significance level of 0.05.

Step 3: Collect sample data
Gather data regarding the video-watching time for a random sample of students at UTeM. Make sure the sample size is sufficiently large (typically, at least 30 observations) to satisfy the assumptions of the hypothesis test.

Step 4: Calculate the test statistic
We will use a one-sample t-test since we have the sample mean and standard deviation. The test statistic is calculated as:

t = (sample mean - population mean) / (sample standard deviation / sqrt(sample size))

In this case, the population mean is 2 (as given in the survey), the sample mean and sample standard deviation should be calculated from the UTeM student data.

Step 5: Determine the critical value or p-value
Using the test statistic, we can either compare it to a critical value from the t-distribution or calculate the p-value associated with the test statistic.

Step 6: Compare the test statistic with the critical value or p-value
If the test statistic falls outside the critical region or the p-value is less than the significance level (α), reject the null hypothesis. Otherwise, fail to reject the null hypothesis.

Step 7: Interpret the result
Based on the conclusion from Step 6, interpret the result in the context of the problem. For example, if we reject the null hypothesis, it would indicate that the average video-watching time for students at UTeM is significantly lower than two hours per day.

Remember to perform appropriate calculations based on the data collected and the available statistical software to ensure accuracy in the hypothesis test.