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60 Cards in this Set
- Front
- Back
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Define descriptive statistics
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summarize data w/ charts, graphs, values etc.
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Define inferential statistics
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make generalizations based on descriptive statistics.
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group of elements for which understanding is desired...
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population
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set of conditions that repeatedly come together to transform inputs or outputs...
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process
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subset of a population or process...
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sample
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number summarizing some aspect of a population or process- descriptive measure of a population...
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parameter
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some number that summarizes some aspect of a sample-descriptive measure of a sample...
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statistic
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using sampling info to learn about a population/process...
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statistical inference
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single characteristic of an object or event...
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statistical variable
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models can be useful in several ways...
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-making better decisions
-communication -understanding concepts -identifying relationships |
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how do you know which concept or technique to apply to a given situation..?
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1)identify the purpose/objective
2)identify the type of data |
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the data values are measured by meaningful numbers that tell how much and how many...
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quantitative data
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data values are placed in classes and have no natural ordering...
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qualitative data
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the way observations are spread out across a range of values...
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distribution
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a table that tabulates the number of occurences or counts of a particular variable
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frequency table
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frequency table group that covers a particular range of values...
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bin
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chart in which each bar represents a particular bin...
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histogram
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A cumulative relative frequency must total...
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1 (one)
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pth percentile...
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value in a distribution such that p% of the distribution is less than or equal to that value.
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values located at the 25th, 50th, and 75th percentiles are...
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quartiles
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interquartile range (IQR)
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central range. contains middle 50% of data
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the sum of the numerical observations divided by the total number of observations...
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arithmetic mean
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the middle value...
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median
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most frequently occurring value...
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mode
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the distance between the largest and smallest values within a data set...
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range
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Difference between MAD, variance, std. deviation, coefficient of variation
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?
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What should population and sample be matched with?
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Parameter and statistic
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do we divide by n-1 for populations or samples?
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samples
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Do you need the mean to calculate variability? Do you need the variability to calculate the mean?
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Yes, no
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Explain the significance of the following percentages: 68, 95, 99.7
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-68% of data values lie within one std. dev of the mean
-95% lie within 2 std devs -99.7% lie within 3 std devs |
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standard deviation divided by the mean results in..
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the coefficient of variation
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measure of the lack of symmetry in the distribution of data values...
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skewness, a skewness of 0 means its symmetric
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measure of heaviness of tails in distribution...
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kurtosis
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more extreme values then expected...
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positive kurtosis
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less extreme values than expected...
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negative kurtosis
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name two values that a boxplot does not show...
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mean and standard deviation
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... tells us what can happen and with what likelihood
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probability,
general --> specific |
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... looks at what happened and tries to generalize about how the world works
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statistical inference, specific --> general
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is the process of obtaining information through observation or measurement of a phenomenon whose outcomes are not certain
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random experiment
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the most basic possible outcomes of an experiment, cannot be broken down into smaller occurrences...
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simple events
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collection of all simple events...
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sample space, outcomes must be mutually exclusive and exhaustive
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subset of a sample space
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event
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two events are mutually exclusive if...
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the occurrence of one event excludes the occurrence of another. i.e., they can't both happen at the same time.
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complement of A is...
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Not A
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theoretical approach
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-#of ways of obtaining event/total # of equally liely possible outcomes
-no experiment |
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Relative frequency
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#of times an event occurs/# of replications
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subjective assessment
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-conditions cannot be replicated
-probability represents an individual's judgement |
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discrete probability distribution
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consists of whole numbers or counts
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continuous probability distribution
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theoretically an infinite # of outcomes within a given range
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What are the two requirements for a discrete probability distribution?
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-probs must be between 0 and 1.
-sum of probs must = 1 |
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a variable whose values occur at random, following a probability distribution
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random variable
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what are the two requirements of a random variable
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-numerical values
-probs associated w/ those values (probs need not be equal) |
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how do you find the expected value?
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sigma (x*P(x))
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sample selected in such away that each member of the population has an equal and inpdepenedent chance of being selected
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simple random sample
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randomly select first, than all chances are equal
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systematic random sample
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splitting population into non-overlapping subpopulations and draw from each
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stratified random sample
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self-selected non-random sample
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ex: calling in, internet
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judgement non-random sample
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ex: pick target cities
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convenience non-random sample
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ex: street corner
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advantages to sample over census
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cost/time savings, accuracy, destruction testing
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