Consider the three stocks in the following table. P(t) represents price at time t, and Q (t) represents share outstanding at time t. Stock C splits two for one in the last period.
|
P(0) |
Q(0) |
P(1) |
Q(1) |
P(2) |
Q(2) |
|
|
A |
90 |
100 |
95 |
100 |
95 |
100 |
|
B |
50 |
200 |
45 |
200 |
45 |
200 |
|
C |
100 |
200 |
110 |
200 |
55 |
400 |
First, calculate the price weighted indexes at t=0 and t=1. Based on the two numbers calculate the rate of return.
What must happen to the divisor for the price-weighted index in year 2?
Calculate the price weighted index at t=2. Based on the index number at t=1 and t=2, calculate the rate of return.
In: Finance
1.Match the synonyms.
-leverage
-cost of capital
-expected return
-intrinsic value
-No Arbitrage
-arbitrage profit
-NPV of future investments
synonym bank: required return debt fundamental value free lunch growth options expected holding period return (HPR) Law of One Price
2.The difference between the expected return and the cost of capital for a stock is called (one word)
3.A stock with a negative alpha is ?
4.A firm has 5 million shares outstanding, trading at $20 per share, and $30 million in debt. The market capitalization is:
5.The market value of a company is always equal to the market value of the assets in place.(T/F)
6.A market in which stock prices reflect all available information is called a(n)_________ capital market.
7.we learn several equivalent statements that describe a well-functioning capital market:
a. The current market price of any security is equal to the (two words) _______ ________ .
b. The alpha of any security is (one word or number) _________ .
c. The NPV of investing on the capital market is (one word or number)__________ .
d. The expected return on any security is equal to the (three words at most)______ ______ _______ .
In: Finance
The State of Florida is considering raising the fine for red light violations this session. The theory, of course, is that higher fines deter violations. You decide to test this by taking a sample of ten states and record their 2003 state fine for running a red light and the number of cited violations per 1,000 vehicle miles (standard measure in transportation to control for highway volume). Assume enforcement is relatively equal across the states:
State Fine Violations Measure
50 10
100 8
120 9
40 7
80 10
60 12
90 7
100 8
50 9
110 2
1.State your null formally and in lay terms for a simple regression
2. Calculate r and the regression line (y = a + bx) and reject/accept at a=.05.
3. Explain your findings in lay terms using b (if relevant), r, r-square, and p-value.
4.Calculate a 95% confidence interval for the slope and explain in layterms.
5. Calculate a 95% confidence interval for Y when X is 80,
explain in layterms.
In: Statistics and Probability
A teacher is trying to assign grades so that she has the following distribution:
| Grade | % of Class |
| A | 15 |
| B | 30 |
| C | 40 |
| D | 10 |
| F | 5 |
This is what she actually has in her grade book:
| Grade | # Students |
| A | 20 |
| B | 40 |
| C | 35 |
| D | 8 |
| F | 8 |
At a significance level of 0.05, are these two distributions different? Include either χ2 or the p-value to justify your answer.
In: Statistics and Probability
5. Penn State University wants to determine if students are satisfied with the dorm conditions. A researchers takes random samples of 25 students from each year and the students are asked whether or not they are satisfied with the dorm conditions. The results of the study are given below:
| Freshman | Sophomores | Juniors | Seniors | |
| Satisfied | 15 | 12 | 9 | 7 |
| Dissatisfied | 10 | 13 | 16 | 18 |
Is there sufficient evidence of a difference in dorm room satisfaction among the various year levels?
| A. |
The data proves that there is a difference in dorm room satisfaction among the various year. |
|
| B. |
There is sufficient evidence at the 1% significance level of a difference in dorm room satisfaction among the various years. |
|
| C. |
There is sufficient evidence at the 5% significance level, but not at the 1% significance level, of a difference in dorm room satisfaction among the various years. |
|
| D. |
With P = 0.1117 there is not sufficient evidence of a difference in in dorm room satisfaction among the various years. |
|
| E. |
There is not enough information to answer this question. |
6. When analyzing survey results from a two way table, the main distinction between a test of independence and a test for homogeneity is:
| A. |
How the degrees of freedom are calculated |
|
| B. |
how the expected counts are calculated |
|
| C. |
the number of samples obtained |
|
| D. |
the number of rows in the two way table |
|
| E. |
the number of columns in the two way table. |
7. A controversial issue in the sport of professional soccer is the use of instant replay for making difficult goal line devisions. Each person in a representative sample of 102 players, fans, coaches, and officials was asked his or her opinion about the use of instant replay for goal line decisions. The data are summarized in the two way frequency table below.
| Opinion | |||
| Category | Favor Use | Oppose Use | |
| Players | 22 | 2 | |
| Fans | 18 | 6 | |
| Coaches | 15 | 26 | |
| Officials | 3 | 10 |
In testing to see whether opinion with respect to the use of instant replay is independent of the category of the person interviewed, a chi square test statistic of 27.99 and a p value less than 0.001 were calculated which of the following statements is correct?
| A. |
The number of degrees of freedom for the test is 8 - 1 = 7 |
|
| B. |
The chi square test should not have been used because two of the counts in the table are less than 5. |
|
| C. |
The null hypothesis sates that there is an association between category and opinion about the use of instant replay, and the small p value suggests that the null hypothesis should be rejected. |
|
| D. |
The small p value suggests that there is evidence of an association between category and the opinion about the use of instant replay. |
|
| E. |
The chi square test shows that fans favor the use of instant replay. |
8.
A controversial issue in the sport of professional soccer is the use of instant replay for making difficult goal line devisions. Each person in a representative sample of 102 players, fans, coaches, and officials was asked his or her opinion about the use of instant replay for goal line decisions. The data are summarized in the two way frequency table below.
| Opinion | |||
| Category | Favor Use | Oppose Use | |
| Players | 22 | 2 | |
| Fans | 18 | 6 | |
| Coaches | 15 | 26 | |
| Officials | 3 | 10 |
In testing to see whether opinion with respect to the use of instant replay is independent of the category of the person interviewed, a table of respective frequencies is found. In this table the expected number of professional baseball players opposing the use of instant replay is equal to:
| A. |
10.4 |
|
| B. |
24.1 |
|
| C. |
11 |
|
| D. |
6 |
|
| E. |
8.4 |
9. A study was performed to examine personal goals of children in grades 4, 5, and 6. A random sample of students was selected in Virginia. The students received a personal questionaire regarding achieveing personal goals. They were asked what they most like to do at school: make good grades, be good at sports, or be popular. The results are presented in the table below by sex of the child.
| Boys | Girls | |
| Make good grades | 96 | 295 |
| Be popular | 32 |
45 |
| Be good at sports | 95 | 40 |
What type of test is appropriate for this situation?
| A. |
Chi square goodness of fit |
|
| B. |
Chi square test for independence |
|
| C. |
Chi square test for homogeneity |
|
| D. |
Two sample t test for difference in means |
|
| E. |
Two sample z test for difference in proportions |
10.
Recent revenue shortfalls in a midwestern state led to a reduction in the state budget for higher education. To offset the reduction, the largest state university proposed a 25% tuition increase. It was determined that such an increase was needed simply to compenstate for the lost support from the state. Separate random samples of 50 freshmen, 50 sophomores, 50 juniors, and 50 seniors from the university were asked whether they were strongly opposed to the increase, given that it was the minimum increase necessary to maintain the university's budget at current levels. Here are the results.
| Strong Opposed | Freshman | Sophomore | Junior | Senior |
| Yes | 39 | 36 | 29 | 18 |
| No | 11 | 14 | 21 | 32 |
Which hypothesis would be appropriate for performing a chi square test?
| A. |
The null hypothesis that is the closer students get to graduation, the less likely they are to be opposed to tuition increases. The alternative is that how close students are to graduation makes no difference in their opinion. |
|
| B. |
The null hypothesis is that the mean number of students who are strongly opposed is the same for each of the 4 years. The alternative is the mean is the different for at least 2 of the 4 years. |
|
| C. |
The null hypothesis is that the distribution of student opinion about the proposed tuition increase is the same for each of the 4 years at the university. The alternative is that the distribution is different for at least 2 of the 4 years. |
|
| D. |
The null hypothesis is that year in school and student opinion about the tuition increase in the sample are independent. The alternative is that these variables are dependent. |
|
| E. |
The null hypothesis is that there is an association between year in school and opinion about the tuition increase at the university. The alternative hypothesis is that these variables are not associated. |
In: Statistics and Probability
Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings -
|
Income ($1000s) |
Household Size |
Amount Charged ($) |
| 54 | 3 | 4,016 |
| 30 | 2 | 3,159 |
| 32 | 4 | 5,100 |
| 50 | 5 | 4,742 |
| 31 | 2 | 1,864 |
| 55 | 2 | 4,070 |
| 37 | 1 | 2,731 |
| 40 | 2 | 3,348 |
| 66 | 4 | 4,764 |
| 51 | 3 | 4,110 |
| 25 | 3 | 4,208 |
| 48 | 4 | 4,219 |
| 27 | 1 | 2,477 |
| 33 | 2 | 2,514 |
| 65 | 3 | 4,214 |
| 63 | 4 | 4,965 |
| 42 | 6 | 4,412 |
| 21 | 2 | 2,448 |
| 44 | 1 | 2,995 |
| 37 | 5 | 4,171 |
| 62 | 6 | 5,678 |
| 21 | 3 | 3,623 |
| 55 | 7 | 5,301 |
| 42 | 2 | 3,020 |
| 41 | 7 | 4,828 |
| 54 | 6 | 5,573 |
| 30 | 1 | 2,583 |
| 48 | 2 | 3,866 |
| 34 | 5 | 3,586 |
| 67 | 4 | 5,037 |
| 50 | 2 | 3,605 |
| 67 | 5 | 5,345 |
| 55 | 6 | 5,370 |
| 52 | 2 | 3,890 |
| 62 | 3 | 4,705 |
| 64 | 2 | 4,157 |
| 22 | 3 | 3,579 |
| 29 | 4 | 3,890 |
| 39 | 2 | 2,972 |
| 35 | 1 | 3,121 |
| 39 | 4 | 4,183 |
| 54 | 3 | 3,730 |
| 23 | 6 | 4,127 |
| 27 | 2 | 2,921 |
| 26 | 7 | 4,603 |
| 61 | 2 | 4,273 |
| 30 | 2 | 3,067 |
| 22 | 4 | 3,074 |
| 46 | 5 | 4,820 |
| 66 | 4 | 5,149 |
In: Statistics and Probability
Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings -
|
Income ($1000s) |
Household Size |
Amount Charged ($) |
| 54 | 3 | 4,016 |
| 30 | 2 | 3,159 |
| 32 | 4 | 5,100 |
| 50 | 5 | 4,742 |
| 31 | 2 | 1,864 |
| 55 | 2 | 4,070 |
| 37 | 1 | 2,731 |
| 40 | 2 | 3,348 |
| 66 | 4 | 4,764 |
| 51 | 3 | 4,110 |
| 25 | 3 | 4,208 |
| 48 | 4 | 4,219 |
| 27 | 1 | 2,477 |
| 33 | 2 | 2,514 |
| 65 | 3 | 4,214 |
| 63 | 4 | 4,965 |
| 42 | 6 | 4,412 |
| 21 | 2 | 2,448 |
| 44 | 1 | 2,995 |
| 37 | 5 | 4,171 |
| 62 | 6 | 5,678 |
| 21 | 3 | 3,623 |
| 55 | 7 | 5,301 |
| 42 | 2 | 3,020 |
| 41 | 7 | 4,828 |
| 54 | 6 | 5,573 |
| 30 | 1 | 2,583 |
| 48 | 2 | 3,866 |
| 34 | 5 | 3,586 |
| 67 | 4 | 5,037 |
| 50 | 2 | 3,605 |
| 67 | 5 | 5,345 |
| 55 | 6 | 5,370 |
| 52 | 2 | 3,890 |
| 62 | 3 | 4,705 |
| 64 | 2 | 4,157 |
| 22 | 3 | 3,579 |
| 29 | 4 | 3,890 |
| 39 | 2 | 2,972 |
| 35 | 1 | 3,121 |
| 39 | 4 | 4,183 |
| 54 | 3 | 3,730 |
| 23 | 6 | 4,127 |
| 27 | 2 | 2,921 |
| 26 | 7 | 4,603 |
| 61 | 2 | 4,273 |
| 30 | 2 | 3,067 |
| 22 | 4 | 3,074 |
| 46 | 5 | 4,820 |
| 66 | 4 | 5,149 |
In: Statistics and Probability
Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings -
|
Income ($1000s) |
Household Size |
Amount Charged ($) |
| 54 | 3 | 4,016 |
| 30 | 2 | 3,159 |
| 32 | 4 | 5,100 |
| 50 | 5 | 4,742 |
| 31 | 2 | 1,864 |
| 55 | 2 | 4,070 |
| 37 | 1 | 2,731 |
| 40 | 2 | 3,348 |
| 66 | 4 | 4,764 |
| 51 | 3 | 4,110 |
| 25 | 3 | 4,208 |
| 48 | 4 | 4,219 |
| 27 | 1 | 2,477 |
| 33 | 2 | 2,514 |
| 65 | 3 | 4,214 |
| 63 | 4 | 4,965 |
| 42 | 6 | 4,412 |
| 21 | 2 | 2,448 |
| 44 | 1 | 2,995 |
| 37 | 5 | 4,171 |
| 62 | 6 | 5,678 |
| 21 | 3 | 3,623 |
| 55 | 7 | 5,301 |
| 42 | 2 | 3,020 |
| 41 | 7 | 4,828 |
| 54 | 6 | 5,573 |
| 30 | 1 | 2,583 |
| 48 | 2 | 3,866 |
| 34 | 5 | 3,586 |
| 67 | 4 | 5,037 |
| 50 | 2 | 3,605 |
| 67 | 5 | 5,345 |
| 55 | 6 | 5,370 |
| 52 | 2 | 3,890 |
| 62 | 3 | 4,705 |
| 64 | 2 | 4,157 |
| 22 | 3 | 3,579 |
| 29 | 4 | 3,890 |
| 39 | 2 | 2,972 |
| 35 | 1 | 3,121 |
| 39 | 4 | 4,183 |
| 54 | 3 | 3,730 |
| 23 | 6 | 4,127 |
| 27 | 2 | 2,921 |
| 26 | 7 | 4,603 |
| 61 | 2 | 4,273 |
| 30 | 2 | 3,067 |
| 22 | 4 | 3,074 |
| 46 | 5 | 4,820 |
| 66 | 4 | 5,149 |
In: Statistics and Probability
What is the predicted annual credit card charge for a three-person household with an annual income of $40,000 (show your work) -
|
Income ($1000s) |
Household Size |
Amount Charged ($) |
| 54 | 3 | 4,016 |
| 30 | 2 | 3,159 |
| 32 | 4 | 5,100 |
| 50 | 5 | 4,742 |
| 31 | 2 | 1,864 |
| 55 | 2 | 4,070 |
| 37 | 1 | 2,731 |
| 40 | 2 | 3,348 |
| 66 | 4 | 4,764 |
| 51 | 3 | 4,110 |
| 25 | 3 | 4,208 |
| 48 | 4 | 4,219 |
| 27 | 1 | 2,477 |
| 33 | 2 | 2,514 |
| 65 | 3 | 4,214 |
| 63 | 4 | 4,965 |
| 42 | 6 | 4,412 |
| 21 | 2 | 2,448 |
| 44 | 1 | 2,995 |
| 37 | 5 | 4,171 |
| 62 | 6 | 5,678 |
| 21 | 3 | 3,623 |
| 55 | 7 | 5,301 |
| 42 | 2 | 3,020 |
| 41 | 7 | 4,828 |
| 54 | 6 | 5,573 |
| 30 | 1 | 2,583 |
| 48 | 2 | 3,866 |
| 34 | 5 | 3,586 |
| 67 | 4 | 5,037 |
| 50 | 2 | 3,605 |
| 67 | 5 | 5,345 |
| 55 | 6 | 5,370 |
| 52 | 2 | 3,890 |
| 62 | 3 | 4,705 |
| 64 | 2 | 4,157 |
| 22 | 3 | 3,579 |
| 29 | 4 | 3,890 |
| 39 | 2 | 2,972 |
| 35 | 1 | 3,121 |
| 39 | 4 | 4,183 |
| 54 | 3 | 3,730 |
| 23 | 6 | 4,127 |
| 27 | 2 | 2,921 |
| 26 | 7 | 4,603 |
| 61 | 2 | 4,273 |
| 30 | 2 | 3,067 |
| 22 | 4 | 3,074 |
| 46 | 5 | 4,820 |
| 66 | 4 | 5,149 |
In: Statistics and Probability
The following data set shows the number of chirps in one minute from a cricket and the temperature outside (in degrees Fahrenheit):
| Chirps per Minute | Temperature |
|---|---|
| 98 | 58.4 |
| 107 | 67.5 |
| 111 | 54.4 |
| 112 | 67.2 |
| 113 | 68.4 |
| 120 | 62.2 |
| 123 | 76 |
| 129 | 69.3 |
| 137 | 65.9 |
| 140 | 66 |
| 142 | 67.2 |
| 148 | 64.7 |
| 151 | 80.4 |
| 158 | 76.4 |
| 165 | 84.5 |
What is the rank correlation coefficient? (Round to three decimal places.)
What is the critical rho value at a 0.01 significance?
Do we have correlation?
In: Statistics and Probability