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E7-29 (similar to) Question Help The Chemung Corporation manufactures Lamps. It has set up the following standards per finished unit for Assume that there was no beginning inventory of either direct materials or finished units. During the month, direct materials and direct manufacturing labor: materials purchased amounted to 97,500 It, at a total cost of $148,500. Input price variances are isolated (Dick be icon in view the siandards ) upon purchase. Input-officiancy variances are isolated at the time of usage. The number of "nished units budgeted for January 2017 was 9,750; 9,650 units were actually produced. Read the mopurements (Click te kan to view icial dula) Let's begin by calculating the actual input at the budgeted price. [Round your answers to the nearest whole dollar.] Actual input Budgeted prion Cost Direct materials (purchases] 97 400 138 750 Direct material (usagel 05 500 429.750 Dared manufacturing isbor 4 800 30 00 138 090 Next determine the formula and calculate the ensis for the flexible budget Budgeted input for actual output Budgeted price " Fluxible budget poet Diroot materials 95 500 4.50 134.280 Direct manufacturing labor 4 825 30.00 144.750 Now can puts the price and efficiency verdances for direct materials and direct manufacturing labor. Label each variance as favorabie (F) or unfavorable (U). Price Dingof materials Direct manufacturing labor Direct materials: 10 lb. at $4.50 per lb. $ 45.00 Direct manufacturing labor: 0.5 hour at $30 per hour 15.00Actual results in January 201? were as follows: Direct materials: 95,500 lb. used Direct manufacturing labor: 4,600 hours $ 146,050 1. Compute the January 201? price and eiciency variances of direct materials and direct manufacturing labor. 2. Prepare journal entries to record the variances in requirement 1. 3. Comment on the January 201? price and efficiency variances of Chemung Corporation. 4. Whyr might Chemung calculate direct materials price variances and direct materials efficiency variances with reference to different points in time? The Seneca Corporation manufactures lamps. It has set up the following standards per finished unit for direct materials and direct manufacturing labor, (Click the icon to view the standards. ) The number of finished units budgeted for January 2014 was 9,910, 9,900 units were actually produced (Click the icon to view actual data ) Assume that there was no beginning inventory of either direct materials or finished units. During the month, materials purchases amounted to 99, 100 lb, at a of $515.320. Input price variances are isolated upon purchase. Input efficiency variances are isolated at the time of usage. Read the requirements. Requirement 1. Compute the January 2014 price and efficiency variances of direct materials and direct manufacturing labor. Let's begin by calculating the actual input at the budgeted price. (Round your answers to the nearest whole dollar ) Actual input X Budgeted price E Cost Direct materials (purchases) Direct materials (usage) Direct manufacturing labor Next determine the formula and calculate the costs for the flexible budget Flexible budget cost Direct materials Direct manufacturing labor Now compute the price and efficiency variances for direct materials and direct manufacturing labor. Label each variance as favorable (F) or unfavorable (U). Choose from any list or enter any number in the input fields and then continue to the next question.Data Tableh Direct materials: 10 lb. at $5.00 per lb $ 50.00 Direct manufacturing labor: 0.5 hour at $30 per hour 15.00 Print Done Actual results in January 2014 were as follows: Direct materials: 97,000 lb. used Direct manufacturing labor: 4,900 hours $ 154,350A researcher has data on class size (CS) and average test scores from 100 econometrics classes (TS). He estimates the OLS regression and obtains the following regression line: TS = 520.4-5.82 x CS reg (20.4) (2.21) where the R2 = 0.08, SER = 11.5, and the standard errors of each coefficient is in parentheses underneath. inf a) What are Bo and B1, and what are their standard errors? 51 b) Interpret the R for this regression. c) A classroom has 22 students. What is the regression's prediction for that classroom's average test score? d) Last year a classroom had 19 students and this year it has 23 students. What is the regression's prediction for the change in the classroom average test score? (Hint: A change of 1 unit of X induces a change of B 1 units in Y, so a change in 4 units of X will induce what change in Y?) e) The sample average class size across the 100 classrooms is 21.4. What is the sample average of test scores across the 100 classrooms? (Hint: The estimated regression line (above) gives you the average relationship between Y and X!) f) Is Bi significant at the 5% significance level (i.e. can you reject the null that B 1 = 0)? (Hint: Same procedure as 4b where the critical value is now for 98 degrees of freedom at the 5% level-see Table 2) . g) Construct a 95% confidence interval for 1, the regression slope coefficient.3. An economics department at a large state university keeps track of its majors' starting salaries. Does taking econometrics affect starting salary? Let SAL = salary in dollars, GPA = grade point average on a 4.0 scale, METRICS = 1 if student took econometrics, and METRICS = 0 otherwise. Using the data file metrics.dat, which contains information on 50 recent graduates, we obtain the estimated regression SAL = 24200 + 1643GPA + 5033METRICS R= = 0.74 (se ) (1078) (352) (456) (a) Interpret the estimated equation. (b) How would you modify the equation to see whether women had lower starting salaries than men? (Hint: Define an indicator variable FEMALE = 1, if female; zero otherwise.) (c) How would you modify the equation to see if the value of econometrics was the same for men and women?1. Consider the simple regression model: Vi = Bo+ Biri + Hi, for i = 1, ... . n, with E(uilz,) - 0 and let a be a dummy instrumental variable for I, such that we can write: Ci =not matu with E(uilz;) = 0 and E(viz) =0. (c) Denote by no, the number of observations for which = = 0 and by n, the number of observations for which a, = 1. Show that: (a - 2) = =(n-m). 1=1 and that: [( - =)(y: - 9) = -(n - n) (31 - 30) . where to and g are the sample means of y for z equal to 0 and 1 respectively. ( Hint: Use the fact that n = nj + no, and that = = m). (d) Now we regress y on i to obtain an estimator of &. From the standard formula of the slope estimator for an OLS regression and using the result in (c), show that: B - 91 -90 $1 - To This estimator is called the Wald estimator.