Contents 1. Introduction: The Need for Error Detection 3 1.1 Error detection process 3 1.2 Types of errors 4 1.2.1 Single bit error 4 1.2.2 Burst error 4 2. Cyclic Redundancy Check 4 2.1 Background 4 2.2 Idea behind the CRC 5 2.3 CRC Algorithm 5 2.3.1 Modulo 2 Arithmetic 6 2.3.2 Polynomial representation 8 2.3.3 Digital Logic 9 2.4 Why CRC works 10 3. The Generator Polynomial and Error Detection Capabilities 10 3.1 Kinds of error CRC detects 10 4. References 11 1
Words: 2530 - Pages: 11
35353 Regression Analysis Mini Conference Report Interest Rate Movement in Australia Analysts: Conrad Gutierrez – 10169050 Contents page: Introduction 3 Methodology 4 Multiple Linear Regression 4 * Model Assumptions 4 Full Model 5 New Full Model 7 Finding the Best Model * Method 1: Stepwise Regression 9 * Method 2: Forward Selection 11 * Method 3: Backward Elimination 12 * Method
Words: 7765 - Pages: 32
Running Head: Case 49 Property Crimes Andrea K. Wallace GM533 Professor Beintema Keller Graduate School of Management October 16, 2011 Executive Summary After examining the eight variables that attribute to property crimes, the three variables that effect crime are density, dropout and urban. When density increases by 1%, this would cause a decrease in crime rate. When the dropout rate increases by 1%, this would cause an increase in property crimes. When urban area crimes increase
Words: 3708 - Pages: 15
Neural correlates of interspecies perspective taking in the post-mortem Atlantic Salmon: An argument for multiple comparisons correction Craig M. Bennett1, Abigail A. Baird2, Michael B. Miller1, and George L. Wolford3 1 3 Psychology Department, University of California Santa Barbara, Santa Barbara, CA; 2 Department of Psychology, Vassar College, Poughkeepsie, NY; Department of Psychological & Brain Sciences, Dartmouth College, Hanover, NH INTRODUCTION With the extreme dimensionality of functional
Words: 901 - Pages: 4
squares regression, the regression line is obtained by minimizing, a) The total variation in the dependent variable. b) The sum of squares for error (SSE). c) The sum of squares for regression (SSR) d) The sum of squares for total (SST). e) None of the above 2. In a simple regression analysis involving 25 data points, the standard error of estimate is calculated as S( = 2.0 and the Fts = 10, then the information from regression line (SSR) should be, a) 60 b) 50 c) 40 d) 30
Words: 1807 - Pages: 8
Question 1 (a) rc, t is the increase rate of real US private consumption. re, t is the real return of the share price index of the New York Stock Exchange after CPI adjustment. rf, t is the real return of the Long-term government bond yield after CPI adjustment. (b) The plotting graph indicated that there is no obvious trend of the increase rate of real US private consumption. The rate reached its lowest point in 1974. There is no clear trend of real return of the share price index of
Words: 1496 - Pages: 6
Delta Song Case Analysis Possible cost drivers that will allow us to estimate a salary cost function for Delta are: available seat miles, number of departures, available ton miles, revenue passenger miles, and revenue ton miles. The two cost drivers we chose were revenue passenger miles and available ton miles. The salaries consist of payments to pilots, flight attendants and ticket agents. Their salaries are determined by the number of passengers and cargoes and the miles or hours flown. This is
Words: 834 - Pages: 4
| |Mean |61.18787879 | |Mean |1.636666667 | |Standard Error |0.169935661 | |Standard Error |0.14591768 | |Median |62.3 | |Median |1.13 | |Mode
Words: 1210 - Pages: 5
indicating that the two variables are related. First Regression analysis: Regression Equation: National health expenditures = - 161.1464 + 0.1677 * Gross domestic product R | 0.99297 | R Square | 0.98599 | t Statistic | 58.12474 | Standard Error | 88.03083 | p-value | 0.0000000000905707 | This shows a strong positive correlation between the two variables, based on both the large value of the t statistic and the small p-value. From my data set, there are no specific outliers which make
Words: 1797 - Pages: 8
Multiple R 0.022301 R Square 0.000497 Adjusted R Square -0.0093 Standard Error 0.656922 Observations 104 ANOVA df SS MS F Significance F Regression 1 0.021902 0.021902 0.050753 0.822209 Residual 102 44.01771 0.431546 Total 103 44.03962 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.270871 0.348709 15.11541 8.66E-28 4
Words: 910 - Pages: 4
