LABOR COST VARIANCE CAN BE SPLIT INTO • Direct labor rate variance (P) Calculation: actual total labor costs - (total actual labor hours worked x budgeted labor hour rate) Interpretation: calculates the portion of labor costs variance driven by the changed labor rate per hour Possible reasons for variances: changes in staff qualification and skills‚ general increase of wages in economy‚ premiums paid to finish a job quickly‚ poor budgeting • Direct labor quantity (efficiency) variance (P) Calculation:
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Chapter 14 Factor analysis 14.1 INTRODUCTION Factor analysis is a method for investigating whether a number of variables of interest Y1 ‚ Y2 ‚ : : :‚ Yl‚ are linearly related to a smaller number of unobservable factors F1‚ F2‚ : : :‚ Fk . The fact that the factors are not observable disquali¯es regression and other methods previously examined. We shall see‚ however‚ that under certain conditions the hypothesized factor model has certain implications‚ and these implications in turn
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CHI-SQUARE TEST (χ²): Chi-square is a statistical test commonly used to compare observed data with data we would expect to obtain according to a specific hypothesis. For example‚ if‚ according to Mendel’s laws‚ you expected 10 of 20 offspring from a cross to be male and the actual observed number was 8 males‚ then you might want to know about the "goodness to fit" between the observed and expected. Were the deviations (differences between observed and expected) the result of chance‚ or were they
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and controlling of the project costs. The Project Manager and Project Sponsor will review the following earned value measurements: 1. Schedule Variance (SV) 2. Cost Variance (CV) 3. Schedule Performance Index (SPI) 4. Cost Performance Index (CPI) 5. To Complete Cost Performance Index (TCPI) 6. Estimated Actual Cost at Completion (EAC) Schedule Variance (SV) is a measurement of the schedule performance for a project‚ and is calculated by subtracting the Planned Value (PV) from Earned Value (EV)
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3.0 Variance Analysis 3.1 Flexible-Budget Variance Analysis In Barnes Scuba Diving case‚ the main comparison for the flexible-budget variance analysis would be between the actual results and flexible budget. Static budget would not be useful for this comparison due to the different sales unit output which may result in a misleading and inaccurate result comparison. With reference to the Flexible Budget Section attached in Annex X‚ Flexible-Budget Variance for Revenues was identified to be a favourable
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corrective actions or commend things that resulted in a favorable overall variance. This year‚ the division has a favorable operating income variance of $71‚700. Highlights: · Jim Peterson‚ president of the ice cream division‚ asked Frank‚ vice-president of the Sales and Marketing of the Ice Cream Division to make a short presentation at the next management meeting commenting on the major reasons for the favorable operating income variance of $71‚700 · Using the newly installed financial planning and control
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Data Analysis Descriptive Statistics‚ Estimation‚ Regression & Correlation Treatment Effects of a Drug on Cognitive Functioning in Children with Mental Retardation and ADHD Hossam Elhowary MATH-1016-15 Dr. Maria DeLucia December 09‚ 2014 Introduction The purpose of this survey was to investigate the cognitive effects of stimulant medication in children with mental retardation and Attention-Deficit/Hyperactivity Disorder. Twenty four children were given various dosage of a drug a placebo and
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removed because it results in a higher correlation than TV. Part C After careful analysis of the data during part B‚ the remaining variables are: TV‚ Gas Price‚ Ave. # of Sales people‚ Ave. Rebate‚ and Corporate Sponsored Sales Promo. Each of these independent variables passed all five hurdles and can move on to the final model. It is still imperative that the P- values be analyzed. Table 5: Regression Analysis Coefficients Standard Error t Stat P-value Intercept 278.028 10
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Mean-Variance Analysis Mean-variance portfolio theory is based on the idea that the value of investment opportunities can be meaningfully measured in terms of mean return and variance of return. Markowitz called this approach to portfolio formation mean-variance analysis. Mean-variance analysis is based on the following assumptions: 1. All investors are risk averse; they prefer less risk to more for the same level of expected return. 2. Expected returns for all assets are known. 3. The
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standard deviation (variances are equal). Confidence interval: df for t-multiple is (df1 + df2)‚ or (n1 – 1) + (n2 - 1) Pooled estimate of common standard deviation: SE of difference between two sample means ------------------------------------------------- Confidence interval for differences in sample means when variance is not equal. ------------------------------------------------- df for t-multiple is given by complex formula not shown in book when variance is not equal. Use StatTools
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