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Exam 2 - Flashcards

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Class:MKTG 4154 - Marketing Research
Subject:Marketing
University:Virginia Polytechnic Institute And State University
Term:Spring 2013
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Descriptive Statistics describes characteristics of population
Inferential Statistics Draws conclusions about whole populations from a sample
Frequency Distribution A set of data organized by summarizing the number of times a value occurs
Percentage Distribution A frequency distribution organized into a table or graph summarizing % values
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Probability The long run relative frequency with which an event will occur (adds up to 1)
Proportion a percentage of elements that meet some criterion
Top-Box scores proportion of respondents who chose the most positive choice
  • the portion that would most likely recommend a business or make a purchase
Deviation scores indicates how far an observation is from the mean
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Variance A measure of dispersion.
  • its square root is standard deviation
Standard deviation The index of distributions spread
Normal distribution 99% of its values are within 3 standard deviations from the mean
Standardized normal distribution purely theoretical probability distribution that reflects a normal curve for the standardized value, z
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Characteristics of standardized normal distribution
  1. symmetrical about the mean
  2. mean identifies that normal curves high point (mode)
  3. normal curve has an infinite number of cases (continuous distribution) and area under curve has probability density of 1
  4. Has mean of 0 and standard deviation on 1
Standardized values used to compare an individual value to the population mean in units of the standard deviation

= value to be transformed- mean / standard deviation
Sampling distribution a probability distribution of sample means for all possible samples of a certain size drawn from a particular population
Standard error of the mean the standard deviation of the sampling distribution
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Central limit theorem as a sample size increases, the distribution of approaches normal distribution
Point estimates an estimate of the population mean in the form of a single value, usually the sample mean
confidence interval estimate a specified range of numbers within which a population mean is expected to lie
  • An estimate of the population mean based on the knowledge that it will be equal to the sample mean, plus or minus a small sampling error
Confidence level a percentage that tells how confident a researcher can be about being correct
  • traditionally, researchers use 95% confidence level with 5% tolerance of error
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Random sampling error varies with samples of different sizes
diminishing returns a random sampling error is inversely proportional to the square root of n
heterogenous/homogenous heterogeneous population: has more variance and requires a larger sample
Homogeneous population: has less variance, a smaller standard deviation, and permits a smaller sample
Magnitude of error aka confidence interval
How precise must an estimate be?
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sequential sampling conducting a pilot study to estimate the population parameters so that another, larger sample of appropriate size may be drawn
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 Descriptive Statisticsdescribes characteristics of population
 Inferential StatisticsDraws conclusions about whole populations from a sample
 Frequency DistributionA set of data organized by summarizing the number of times a value occurs
 Percentage DistributionA frequency distribution organized into a table or graph summarizing % values
 ProbabilityThe long run relative frequency with which an event will occur (adds up to 1)
 Proportiona percentage of elements that meet some criterion
 Top-Box scoresproportion of respondents who chose the most positive choice
  • the portion that would most likely recommend a business or make a purchase
 Deviation scoresindicates how far an observation is from the mean
 VarianceA measure of dispersion.
  • its square root is standard deviation
 Standard deviationThe index of distributions spread
 Normal distribution99% of its values are within 3 standard deviations from the mean
 Standardized normal distributionpurely theoretical probability distribution that reflects a normal curve for the standardized value, z
 Characteristics of standardized normal distribution
  1. symmetrical about the mean
  2. mean identifies that normal curves high point (mode)
  3. normal curve has an infinite number of cases (continuous distribution) and area under curve has probability density of 1
  4. Has mean of 0 and standard deviation on 1
 Standardized valuesused to compare an individual value to the population mean in units of the standard deviation

= value to be transformed- mean / standard deviation
 Sampling distributiona probability distribution of sample means for all possible samples of a certain size drawn from a particular population
 Standard error of the meanthe standard deviation of the sampling distribution
 Central limit theoremas a sample size increases, the distribution of approaches normal distribution
 Point estimatesan estimate of the population mean in the form of a single value, usually the sample mean
 confidence interval estimatea specified range of numbers within which a population mean is expected to lie
  • An estimate of the population mean based on the knowledge that it will be equal to the sample mean, plus or minus a small sampling error
 Confidence levela percentage that tells how confident a researcher can be about being correct
  • traditionally, researchers use 95% confidence level with 5% tolerance of error
 Random sampling errorvaries with samples of different sizes
 diminishing returnsa random sampling error is inversely proportional to the square root of n
 heterogenous/homogenousheterogeneous population: has more variance and requires a larger sample
Homogeneous population: has less variance, a smaller standard deviation, and permits a smaller sample
 Magnitude of erroraka confidence interval
How precise must an estimate be?
 sequential samplingconducting a pilot study to estimate the population parameters so that another, larger sample of appropriate size may be drawn
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