Statistical techniques

Chapter 1  What is statistics? When you have completed this chapter, you will be able to: Explain what is meant by statistics, identify the role of statistics in the development of knowledge and everyday life, explain what is meant by descriptive statistics and inferential statistics, distinguish between a qualitative variable and a quantitative variable,...
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When you have completed this chapter, you will be able to: Organize raw data into frequency distribution; produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data; develop and interpret a stemandleaf display; present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart; detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency.
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When you have completed this chapter, you will be able to: Understand the importance of an appropriate model specification and multiple regression analysis, comprehend the nature and technique of multiple regression models and the concept of partial regression coefficients, use the estimation techniques for multiple regression models,...
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When you have completed this chapter, you will be able to: Conduct the sign test for single and dependent samples using the binomial and standard normal distributions as the test statistics, conduct a test of hypothesis for dependent samples using the Wilcoxon signedrank test, conduct and interpret the Wilcoxon ranksum test for independent samples,...
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Chapter 1  What is statistics? When you have completed this chapter, you will be able to: Understand why we study statistics, explain what is meant by descriptive statistics and inferential statistics, distinguish between a qualitative variable and a quantitative variable, describe how a discrete variable is different from a continuous variable, distinguish among the nominal, ordinal, interval, and ratio levels of measurement.
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Chapter 18  Nonparametric methods: analysis of ranked data. When you have completed this chapter, you will be able to: Conduct the sign test for dependent samples using the binomial and standard normal distributions as the test statistics, conduct a test of hypothesis for dependent samples using the Wilcoxon signedrank test, conduct and interpret the Wilcoxon ranksum test for independent samples,...
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Chapter 19  Statistical process control and quality management. In this chapter, the learning objectives are: Discuss the role of quality control in production and service operations; define and understand the terms chance cause, assignable cause, in control, out of control, attribute, and variable; construct and interpret a pareto chart; construct and interpret a fishbone diagram; construct and interpret mean and range charts;...
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We describe a statistical technique for assigning senses to words. An instance of a word is assigned a sense by asking a question about the context in which the word appears. The question is constructed to have high mutual information with the translation of that instance in another language. When we incorporated this method of assigning senses into our statistical machine translation system, the error rate of the system decreased by thirteen percent. language model does not realize that take my own decision is improbable because take and decision no longer fall within a single trigram. ...
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When you finish this chapter, you should be able to: Discuss the general idea of analysis of variance, discuss the general idea of analysis of variance, conduct a test of hypothesis to determine whether the variances of two populations are equal, organize data into a oneway and a twoway ANOVA table.
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After studying this chapter you will be able to understand: Describe the term index, understand the difference between a weighted and an unweighted index, construct and interpret a Laspeyres’ price index, construct and interpret a Paasche’s price index, construct and interpret a value index, explain how the consumer price index is constructed and interpreted.
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In this chapter, you learned to: Define the terms state of nature, event, decision alternatives, payoff, and utility; organize information in a payoff table or a decision tree; compute opportunity loss and utility function; find an optimal decision alternative based on a given decision criterion; assess the expected value of additional information.
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The literature concerning the application of statistics to linguistic problems and in particular to mechanical translation is reviewed. The conclusion is that much of the work done is of little direct use for mechanical translation, and that some of it is based on a misapprehension of what statistical techniques can in fact do.
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When you have completed this chapter, you will be able to: Calculate the arithmetic mean, the weighted mean, the median, the mode, and the geometric mean of a given data set; identify the relative positions of the arithmetic mean, median and mode for both symmetric and skewed distributions; point out the proper uses and common misuses of each measure; explain your choice of the measure of central tendency of data; explain your choice of the measure of central tendency of data.
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When you have completed this chapter, you will be able to: Compute and interpret the range, the mean deviation, the variance, the standard deviation, and the coefficient of variation of ungrouped data;
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In this chapter, you will learn to: Explain the terms random experiment, outcome, sample space, permutations, and combinations; define probability; describe the classical, empirical, and subjective approaches to probability; explain and calculate conditional probability and joint probability;...
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When you have completed this chapter, you will be able to: Define the terms probability distribution and random variable; distinguish between discrete and continuous random variables; calculate the mean, variance, and standard deviation of a discrete probability distribution; describe the characteristics and compute probabilities using the Poisson probability distribution.
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When you have completed this chapter, you will be able to: Explain how probabilities are assigned to a continuous random variable, explain the characteristics of a normal probability distribution, define and calculate z value corresponding to any observation on a normal distribution, determine the probability a random observation is in a given interval on a normal distribution using the standard normal distribution, use the normal probability distribution to approximate the binomial probability distribution.
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Chapter 8 provides knowledge of sampling methods and central limit theorem. When you have completed this chapter, you will be able to: Explain under what conditions sampling is the proper way to learn something about a population, describe methods for selecting a sample, define and construct a sampling distribution of the sample mean,...
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In this chapter you will learn: Define a point estimator, a point estimate, and desirable properties of a point estimator such as unbiasedness, efficiency, and consistency; define an interval estimator and an interval estimate; define a confidence interval, confidence level, margin of error, and a confidence interval estimate;...
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When you have completed this chapter, you will be able to: Define null and alternative hypothesis and hypothesis testing, define Type I and Type II errors, describe the fivestep hypothesis testing procedure, distinguish between a onetailed and a twotailed test of hypothesis,...
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