Exam 6: Central Tendency
Exam 1: Why Statistics for Public Managers and Policy Analysts20 Questions
Exam 2: Research Design24 Questions
Exam 3: Conceptualization and Measurement22 Questions
Exam 4: Measuring and Managing Performance: Present and Future21 Questions
Exam 5: Data Collection22 Questions
Exam 6: Central Tendency18 Questions
Exam 7: Measures of Dispersion18 Questions
Exam 8: Contingency Tables16 Questions
Exam 9: Getting Results14 Questions
Exam 10: Introducing Inference: Estimation From Samples20 Questions
Exam 11: Hypothesis Testing With Chi-Square20 Questions
Exam 12: The T-Test20 Questions
Exam 13: Analysis of Variance Anova15 Questions
Exam 14: Simple Regression18 Questions
Exam 15: Multiple Regression29 Questions
Exam 16: Logistic and Time Series Regression21 Questions
Exam 17: Survey of Other Techniques26 Questions
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The mean is often used when analyzing continuous variables.
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True
The mean is a commonly used statistic involving nominal variables.
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False
The mode is defined as the most frequent (typical) value(s) of a variable.
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True
The location of the median is half the distance from the observation with the average value.
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It is common practice to assume that unexamined data usually contain various errors that must be identified and removed.
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Data input is the process of identifying and removing reporting and recording errors.
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Data coding is the process of preparing data for input into statistical software programs.
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Univariate, descriptive statistics are sometimes also called summary statistics.
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The median should always be used when a few very large or very small values affect estimates of the mean.
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Problems pertaining to the data can complicate calculations of the mean.
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Summary statistics are used to highlight important features about unusual observations.
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The mean is defined as the sum of a series of observations, divided by the number of observations of an array.
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Examples of the median are common in demographic studies of income.
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When data are missing, a common practice is to estimate their values and include them in data analysis.
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