wgu: Domain: Mathematics Content (5-9) Subdomain: Part IV: Statistics and Probab
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| show | the number of possible values is either finite number or a countable number # of eggs laid by a chicken
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| Continuous (numerical)data | show 🗑
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| Quantative data | show 🗑
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| Qualatative (categorical or attribute) data | show 🗑
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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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| Census | show 🗑
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| show | Subset of a population
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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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| Data | show 🗑
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| Population | show 🗑
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| show | Collection of data from every member of a population
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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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| Parameter | show 🗑
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| show | a numerical measurement describing some characteristic of a sample.
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| show | numbers representing counts or measurements. Example: The weights of supermodels
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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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| show | Subcollection of members selected from a population
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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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| show | like ordinal but diffence in values is meanighfyl no natura zero Ex years 1000,2000,1776,1492
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| Ratio Level of measurement | show 🗑
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| show | categories only
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| show | categories with some order
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| show | differences but no natural starting point
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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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| show | Conclusion should not be made on small samole size EX: Suspension rate based only on three students
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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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| Experiment | show 🗑
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| show | subjects in experiment
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| Cross sectional study | show 🗑
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| Retrisoectuve (case Control) study | show 🗑
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| show | data are collected in the future from groups (called cohorst )sharing common factors.
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| show | occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors.
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| Blinding | show 🗑
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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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| Replication | show 🗑
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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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| Simple Random Sample (of size n) | show 🗑
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| Systematic Sampling | show 🗑
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| Convience Sampling | show 🗑
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| Stratified Sampling | show 🗑
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| show | divide the population into sections (clusters); randomly select some of those clusters; choose all members from selectd clusters. Ex choose 3 of 20 precints and interview every body in those precints.
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| show | Random Systematic Convenience Stratified Cluster
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| Sampling error | show 🗑
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| Nonsampling error | show 🗑
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