精華區beta NTU-Exam 關於我們 聯絡資訊
課程名稱︰統計學下 課程性質︰工管系必修 課程教師︰蔣明晃 開課系所︰工管系 考試時間︰95/05/01 14:00 ~ 17:00 試題 : I.Multiple Choice Question 1. In one-way ANOVA,the amount of total variation that is unexplained is measured by the: a. sum of squares for treatments b. sum of squares for error c. totat sum of squares d. degrees of freedom 2. Which of the following is not true of the F-distribution ? a. Mean and median are equal b. It is skewed to the right c. Its values are always positive d. It is used in ANOVA test 3. A survey will be conducted to compare the grade point averages of high school students from four different school districts. Students are to be randomly selected from each of the four districts and their grade point averages recorded. The ANOVA model most likely to fit this situation is: a. one-way ANOVA b. two-way ANOVA c. randomized block design d. complete 4*4 factorial design 4. When the effect of a level for one factor depends on which level of another factor is present,the most appropriate ANOVA design to use in the situation is the: a. one-way ANOVA b. two-way ANOVA c. randomized block design d. matched pairs design 5. One-way ANOVA is performed on indeoendent samples taken from three normally distributed populations with equal variances. The following summary statistics were calculated: _ n1 = 7 , x1 = 65 , s1 = 4.2 _ n2 = 8 , x2 = 65 , s2 = 4.9 _ n3 = 9 , x3 = 65 , s3 = 4.6 The value of the test ststistics,F,equals: a. 65 b. 24 c. 137 d. 0 6. One-way ANOVA is applied to independent samples taken from three normally distributed populations with equal variances. The folowing summary statistics were calculated: _ n1 = 8 , x1 = 15 , s1 = 2 _ n2 = 10 , x2 = 18 , s2 = 3 _ n3 = 8 , x3 = 20 , s3 = 2 The within-treatments variation equals: a. 137 b. 460 c. 154 d. 60 7. If four confidence interval estimates for the population means were simultaneously constructed with 95% confidence for four independent treatments,the probability that all four intervals would contain the population means would be: a. 0.857 b. 0.815 c. 0.903 d. 0.950 8. Consider the following partial ANOVA table: Source of Variation SS df MS F Treatments 75 * 25 6.67 Error 60 * 3.75 Total 135 19 The numerator and denominator degree of freedom (identified by asterisks) are: a. 4 and 15 b. 3 and 16 c. 15 and 4 d. 16 and 3 9. One-way ANOVA is applied to independent samples taken from three normally distributed populations with equal variances. The folowing summary statistics were calculated: _ n1 = 10 , x1 = 40 , s1 = 5 _ n2 = 10 , x2 = 48 , s2 = 6 _ n3 = 10 , x3 = 50 , s3 = 4 The between-treatments variation equals: a. 460 b. 688 c. 560 d. 183 10. Given that variance of x = 500 , variance of y = 750 , cov(x,y) = 100 , n = 6 The standard error of estimate is: a. 12.247 b. 24.933 c. 30.2076 d. 11.180 11. If the coefficinet of correlation is 0.90,the percentage of the variation in the dependent variable y that is explained by the variation in the independents variable x is: a. 90% b. 81% c. 0.90% d. 0.81% 12. If the coefficinet of correlation between x and y is close to 1.0,this indicates that a. y causes x to happen b. x causes y to happen c. Both a and b are correct answers d. there may or may not be any causal relationship between x and y 13. In regression analysis,if the coefficinet of correlation is -1.0,then: a. the sum of squares for error is -1.0 b. the sum of squares for regression is 1.0 c. SSE and SSR are equal d. SSR and total variation in y are total 14. Given the following data points:(x,y) = (3,3),(4,4),(5,5),(6,6),(7,7),the least squares estimates of the y-intercept the slope are respectively: a. 0 and 1 b. -1 and 0 c. 5 and 5 d. 5 and 0 15. When all the actual values of y and the predicted values of y are equal, the standard error of estimate will be: a. 1.0 b. -1.0 c. 0.0 d. 2.0 16. For the values of coefficient of determination listed below,which one implied the greatest value of the sum of squares for regression given that the total variation in y is 1800: a. 0.69 b. 0.96 c. 96 d. -100 17. Which of the following statistics and precedures can be used to determine whether a linear model should be employed ? a. The standard error of estimate b. The coefficient of determination c. The t-test of the slope d. All of the above are correct answers 18. If we are interested in determining whether two vatiables are linear related,it is necessary to: a. perform the t-test of the slope β1 b. perform the t-test of the coefficient of correlation ρ c. either a or b since they are identical d. calculate the standard error or estimate Sε 19. The least squares method requires that the variance of error variable is a constant no matter what the value of x is. When this reguirement is violated,the condition is called: a. non-independence of ε b. homoscedasticity c. heteroscedasticity d. influential observation 20. In a regression problem the following pairs of (x,y) are given:(3,1), (3,-1),(3,0),(3,-2),(3,2). That indicates that the: a. correlation coefficient is -1 b. correlation coefficient is 0 c. correlation coefficient is 1 II. True-False Question: If the answer is FALSE,correct the sentence to get a full credir 1. We don't need the t-test of μ1-μ2,since the analysis of variance can be used to test the difference between the two population means. 2. In employing the randomized block design,the primary interest lies in reducing sum of squares for block (SSB). 3. The Bonferroni adjustment to Fisher's Least Significant Difference (LSD) multiple comparison method is made by dividing the specified experimentwise Type I error rate by the number of combinations of pairs of population means. 4. The sum of squares for treatments,SST,achieves its smallestvalue (zero) when all the sample sizes are equal. 5. The calculated value of F in a one-way analysis is 7.88. The numerator degree of freedom and denominator degree of freedom are 3 and 9, respectively. The most accurate statement to be made about the p-value is that p-value < 0.01. 6. If all the valuesof an independent variable x are equal,then regressing a dependent variable y on x will result in a coefficient of determination of zero. 7. In a simple linear regression model,testing whether the slope β1 of the population regressing line could be zero is the same as testing whether or not the population coefficient of correlation ρ equals zero. 8. If the coefficient of correlation is -0.81,then the percentage of the variation in y that is explained by the regression line is 81%. 9. The value of the sum of squares for regression SSR can never be larger than the value of sum of squares for error SSE. 10.The regression line y-hot = 2 + 3x has been fitted to the data points (4,11),(2,7),and(1,5). The residual sum of squares will be 10.0. III.Calculations: 1. In a completely randomized design,12 experimental unit were assigned to the first treatment,15 units to the second treatment,18 umits to the third treatment. A partial ANOVA table is shown below: Source of Variation SS df MS F Treatments * * * 9 Error * * 35 Total * * a.Fill in the blanks (identified by asterisks) in the above ANOVA table. b.Test at the 5% significance level to determine if diffrernces exist among the three treatment means. 2. A professor of statistics is trying to determine which of three statistical software is the best for his students. He believes that the time (in hours) it takes a student to master particular software may be influenced by gender. A 3*2 factorial experiment with three replicates was designed,as shown below: Gender Software male female 1 29 26 24 32 20 30 2 32 23 26 31 21 25 3 18 27 20 22 25 30 Extra information:F(α= 0.1,1,12) = 3.177 F(α= 0.1,2,12) = 2.807 a.Fill in the blanks (identified by asterisks) in the above ANOVA table. Source of Variation SS df MS F Software * * * 0.978 Gender * * * Interaction * * 13.389 Error * * 17.778 Total 328.278 b.Is there sufficient evidence at the 10% significance level to infer that the time it takes a student to master software and the gender of the student interact ? c.Test at the 10% significance level to determine if differences exist among male and female student. 3. In order to examine the differences in ages of teachers among five school districts,an educational statistician took random samples of six teachers' ages in each district. The data listed below: Ages of Teachers among Five School District 1 2 3 4 5 41 39 36 45 53 53 48 28 37 55 28 41 29 46 49 45 51 33 48 56 40 49 27 51 48 59 50 26 49 61 The partial ANOVA table is given as follows: Source of Variation SS df MS Treatment Error 40.993 Total 2846.967 a.Test at the 5% significance level to determine if differences in teachers' ages exist among the five districts. b.Use Tukey's multiple comparison method to determine which means differ. c.Use Fisher's LCD procedure with α = .05 to determine which population means differ. 4. A scatter disgram includes the following data points: x│ 3 2 5 4 5 ─┼────────── y│ 8 6 12 10 14 Two regression models are proposed: Model 1 : y-hot = 1.2 + 2.5x Model 2 : y-hot = 5.5 + 4.0x Using the least squares method,which of these regression models provide the better fit to the data ? Why ? 5. Quality of oil is measured in API gravity degree - the higher the degree API,the higher the quality. The table shown below is produced by an expert in the field who believes thats there is a relationship between quality and price per barrel. Oil degree API Price per barrel(in $) 27.0 12.02 28.5 12.04 30.8 12.32 31.3 12.27 31.9 12.49 34.5 12.70 34.0 12.80 34.7 13.00 37.0 13.00 41.0 13.17 41.0 13.19 38.8 13.22 39.3 13.27 A partial computer output follows: ----------------------------------------------------------------------------- Descriptive Statistics Variable N Mean Standard Deviation Degrees 13 34.60 4.613 Price 13 12.730 0.457 ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- Covariance Degree Price Degree 21.281667 Price 2.026750 0.208833 P.S. 21.281667 is variance of degree 0.208833 is variance of price ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- Regression Analysis coefficients Standard Error Intercept 9.4349 0.2867 Degrees 0.095235 0.008220 ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- Analysis of Variance Source DF SS Regression 1 2.3162 Residual Error 11 0.1898 Total 12 2.5060 ----------------------------------------------------------------------------- a. Determine the coefficient of determination and discuss what its value tells you about the two variables. b. Conduct a test of the population coefficient of correlation to determine at the 5% significance level whether a linear relationship exists between the quality of oil and price per barrel. c. Predict with 95% confidence the oil price per barrel for an API degree of 35 d. Identify possible outliers. -- ※ 發信站: 批踢踢實業坊(ptt.cc) ◆ From: 140.112.245.204