Stock and Watson - Introduction to Econometrics - Solutions Essay

So, we should reject the null hypothesis H0. At a 0.05 level of significance level, we conclude that there is a significant difference between the average height for females and the average height for the males.

Question 4 Use the following table to answer the questions that follow: According to the table, the labor force participation rate in this economy is equal to:

t = −3.15 describes the difference between women and men for what variable in this study? Is this value significant? Provide a rationale for your answer.

Please check your numbers again, some of them seem incorrect. For example, how is that possible the subset has a more extended age range than the total sample?

Consider the following scenario in answering questions 5 through 7. In an article appearing in Today’s Health a writer states that the average number of calories in a serving of popcorn is 75. To determine if the average number of calories in a serving of popcorn is different from 75, a nutritionist selected a random sample of 20 servings of popcorn and computed the sample mean number of calories per serving to be 78 with a sample standard deviation of 7.

The t-test is a parametric analysis technique used to determine significant differences between the scores obtained from two groups. The t-test uses the standard deviation to estimate the standard error of the sampling distribution and examines the differences between the means of the two groups. Since the t-test is considered fairly easy to calculate, researchers often use it in determining differences between two groups. When interpreting the results of t-tests, the larger the calculated t ratio, in absolute value, the greater the difference between the two groups. The significance of a t ratio can be determined by comparison with the critical values in a

One-sample t-test are used in the parametric test which analyzes the means of populations. The t-test for independent groups are statistics that relates difference between treatment means to the amount of variability expected between any two samples of data within the same population (Hansen & Myers, 2012). Critical values are used in significant testing provide a range of t distribution that is used in whether a null hypothesis is rejected. Based on the data below as the level of significance is at .05, thus the critical values would fall under ±1.860 and the t value for this is 1.871 would suggest for the null to be rejected as it is greater than the critical value (Privitera, 2015, p. 267). Based on the population mean of 70 there was a mean difference of

b) What is the difference between the mean of the two groups? What is the difference in the standard deviation?

The null hypothesis was that the female and male shoe sizes have an equal mean while the alternative hypothesis was that female and male shoe sizes do not have an equal mean. With the degrees of freedom being 33, the t-statistic is -8.27. The probability that -8.27 is ≤-1.69 is 7.5×10-10 for the one-tailed test. Also, the probability that -8.27 is ≤ ±2.03. is 1.5×10-9 for the two-tailed test. Due to both probabilities being under the alpha value of 0.05, the null hypothesis is rejected, and the alternative hypothesis is accepted at the 95% confidence level.

Step 1: Null Hypothesis: The average (mean) number of years lived in the current home is equal to 8 years.

It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.

For this independent t test, the mean GPAs of 64 females and 41 males were compared. The variables used are (1) gender, and (2) GPA. The predictor, or independent, variable is gender. And the outcome variable is GPA. Gender can only have two values, male or female; this

2. Use simple regression to estimate the salary cost function for Delta Airlines. Comment on the statistical validity and significance of your results. What are the

Run the regression Report your answer in the format of equation 5.8 (Chapter 5, p. 152) in the textbook including and the standard error of the regression (SER). Interpret the estimated slope parameter for LOT. In the interpretation, please note that PRICE is measured in thousands of dollars and LOT is measured in acres.

The regression results of a study on the determinants of the Kenyan exports by Orindi (2010) indicated that explanatory variables namely, the importer’s GDP and population provided most of the explanatory power in the regression. The coefficients of these variables had positive signs consistent with the theoretical expectations. The positive coefficient for the importer’s GDP is due to the fact that as income levels of the importing country increases, so does the country’s demand for imports. The Kenya’s GDP and population were found to be insignificant in the model and hence the two variables were dropped out of the regression model. The distance variable was found to be significant at 5% and had negative sign as was expected. In this study, the distance had been factored in as the proxy for the transportation costs. The distance in this case had inverse relationship with exports. This implied that the further away from the Nairobi the importing country is located the higher the transportation costs. High transportation costs have negative effects on the exports. However the author did not take into consideration of the fact that there are countries which are nearer to Kenya and yet exports to these countries from Kenya are less than countries that are far away from Kenya. This implies that the level of trade between countries that have close proximity will be influenced by other factors such as; income, trade agreements, and similar