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AMDM Statistics

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Ashley Long

on 9 October 2012

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Transcript of AMDM Statistics

definition: the science that deals with the collection, classification, analysis, and interpretation of numerical facts or data Statistics Samples are a small group or subset of the population.
The population is the entire collection of numbers or things to collect data Samples and Populations A parameter is an unknown and usually estimated value used to represent a population.
Assigned greek letters. Parameters and a Statistic Descriptive Statistics Descriptive and
Statistics Definition:
Deals with descriptions.
Data can be observed but not measured.
Colors, textures, smells, tastes, appearance, beauty, etc.
Qualitative = Quality Qualitative Data Definition: Deals with numbers.
Data which can be measured.
Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages, etc.
Quantitative Quantity Quantitative Data 1. Observational Study- type of research that draws a conclusion by comparing subjects of a control group to subjects in a group with no control substance (ex: test with earphones in one class and test completely quiet {this is the control group}
2. Experiment- methodical study of trial and error to obtain a result
3. Simulation- real world experimentation through a process or system over a period of time
4. Survey- a method of collecting data through a question- answer study. Methods for collecting Data Population: Students at SHS
Sample: Students that play sports at SHS A statistic is a quantity that is calculated from a sample of data. assigned roman letters. Parameter: the mean number of subscribers to a magazine
Statistic: You draw a random sample of 100 subscribers and determine that their mean income is $27,500 Parameter=Population Statistic=Sample the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data
It mostly DESCRIBES the data collected and doesn't really allow us to make further conclusions on the data Inferential Statistics: Inferential Statistics are used to make a generalized statement about a sample from a population. For example you can not accurately measure all test scores in the US but you can take a sample from each state of 100 or so and make a general statement of test scores in the US blue shirts
shirts and sweaters Freshman Class Quantitative Statistics:
672 students
394 girls, 278 boys
68% on honor roll
150 students accelerated in mathematics Types of Sampling convenience: researcher uses any subject available to participate
systematic: random sampling using a system; every third girl or every other customer
stratified: dividing the sample groups into even smaller samples and studying each
cluster: samples divided randomly into clusters and then randomly chose one and study it
random: selection random subset (sample) of a population
snowball: existing subjects recruit future subjects in their group of friends
Quota: divided into groups and researcher "randomly" chooses the subjects
purposive: subjects chosen based on a specific characteristic
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