wgu: Domain: Mathematics Content (5-9) Subdomain: Part IV: Statistics and Probab
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on it to display the answer.
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| Discrete Data | show 🗑
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| show | result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, or interuptions. amount of milk from a cow
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| Quantative data | show 🗑
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| show | different categories distinguished into different categories by non numeric characteristic. gender of professional atheletes
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| show | Numerical measurement describing some characteristic of a population. Count entire population the number of redlights working and not in a city
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| Statistic | show 🗑
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| show | Collection of data from every element in a population
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| Sample | show 🗑
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| show | Statistics a collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data
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| show | observations (such as measurements, genders, survey responses) that have been collected
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| Population | show 🗑
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| Census | show 🗑
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| show | is largely about using sample data to make inferences (or generalizations) about an entire population. It is essential to know and understand the definitions that follow.
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| show | a numerical measurement describing some characteristic of a population.
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| show | a numerical measurement describing some characteristic of a sample.
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| Quantitative data | show 🗑
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| show | can be separated into different categories that are distinguished by some nonnumeric characteristic Example: The genders (male/female) of professional athletes
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| show | can further be described by distinguishing between discrete and continuous types.
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| show | result when the number of possible values is either a finite number or a ‘countable’ number (i.e. the number of possible values is 0, 1, 2, 3, . . .) Example: The number of eggs that a hen lays
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| Sample | show 🗑
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| show | characterized by data that consit of names labels no ordering scheme Ex. yes, no, undecided
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| Ordinal level of measurement | show 🗑
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| Interval level of measurement | show 🗑
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| Ratio Level of measurement | show 🗑
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| Nominal | show 🗑
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| show | categories with some order
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| Interval | show 🗑
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| show | differences and a natural starting point
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| show | one in which respondents themselves decide whether to be included Ex: mail in, internet poll
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| Small Samples Size | show 🗑
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| show | 100% is 100% no such thing as 110%
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| show | observing and measuring specific characteristics withour attemping to midify the subjects being studied.
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| show | apply some treatment and observe its effects on the subjects;
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| Experimental units | show 🗑
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| show | data are observed, measued, and collected at one point in time
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| Retrisoectuve (case Control) study | show 🗑
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| Prospective (longitudinal or cohort) study | show 🗑
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| Confounding | show 🗑
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| show | subject does not know if he is receiving a treatment or a placebo.
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| show | groups of subjects with similar characteristics
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| show | subjecrts are put into blocks thrught a process of random selection.
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| Rigorously Controlled Design | show 🗑
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| show | Repetition of an experiment when there are enough subjects to recognize the differences from different treatments.
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| show | use a sample size that is large enought to see the true nature of any effects andsample using appropriate method such as randomeness
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| show | members of the population are selected in such a way that each individual member has an equal chance of being selected
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| show | Subjects selected in such a way that every possible sample of the sme size n has the same chance of being chosen
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| Systematic Sampling | show 🗑
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| show | use results that are easy to obtain
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| Stratified Sampling | show 🗑
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| Cluster Sampling | show 🗑
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| show | Random Systematic Convenience Stratified Cluster
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| show | The difference between a smple result and the true population result; error results from chance sample fluctuations
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| Nonsampling error | show 🗑
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Created by:
hrichey@my.wgu.edu
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