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Statistics Unit 1
Statistics Topic 1-5
| Question | Answer |
|---|---|
| Observational Units | who/what you're collecting information on |
| Variables | the characteristics for which the observational units differ from one another |
| Data | the information you collect about the variable |
| For further analysis, multiple types of variables require _________ | Their own type of graph and/or formula |
| Variability | the phenomenon of a variable taking on different values or categories form observational unit to observational unit. |
| Quantitative Variable | Measures a numerical characteristic such as height. |
| Categorical Variable | Records a group designation such as gender |
| Binary Variable | Is a categorical variable with only two possible categories (ex. male/female) |
| Research Question | Looks for patterns in a variable or compares a variable across different groups or looks for a relationship between variables. |
| What do you ask to determine the variable? | To determine the ________ ask... 1) Does it represent a question that can be asked of each observational unit? 2) Can the value(s)vary from obs. unit to observational unit. |
| Statistics | The science of reasoning from data |
| Fundamental principle of statistics is? | Variability is the __________ of statistics. |
| Write variables so that how they're measured is ________. | Write variables so that how they're measured is clear. |
| Bar Graph | Displays the distribution of a categorical variable. |
| Distribution | Refers to its pattern of variation. |
| Distribution (categorical variable) | Means the variables possible categories and the proportion of responses in each. |
| What is the simplest way to display a categorical variable? | Bar Graph |
| What is the simplest way to display a quantitative variable? | Dotplot Graph |
| Dotplot Graph | useful for displaying the distribution of relatively small data sets of a quantitative variable. |
| Statistical Tendency | Refers to observational units in one group being more likely to be in a certain category (categorical variable) or to have have higher values (quantitative variable) than those in another group. |
| Center of distributions refers to | Statistical Tendency, the most common data |
| Spread in the distribution refers to | Consistency, how data compare |
| Consistency | Refers to how variable, or spread out, the values in a data set are for a quantitative variable. |
| Data can be summarized through | Words, Numbers, Graphs |
| Graphs reveal | how data vary from one another |
| By examining graphs and comparing distributions, you can discover... | statistical tendency |
| _______ is crucial in statistics | Context |
| Two main characteristics of variation | 1) Tendency as it describes the center of a distribution of data 2) Consistency as it describes the spread of a distribution of data. |
| Each dot in a dotplot represents | a different observational unit |
| Axis should be labeled with | the name of the variable |
| Relate comments to the | context |
| The type of variable can restrict your choice of | graphic display |
| Dotplots and Bar graphs are most illuminating when used to | Compare the distribution of a variable between two or more groups. |
| Proportions are numbers between ___ and ___ | 0 and 1 |
| How do you get a % from a proportion? | Multiple by 100. |
| How do you calculate a proportion? | answer divided by total (12 students agreed out of 24 students) |
| When writing your comments on data, relate your comments to the 1)___ and 2)_____ and make sure ______. | 1)Context of the data 2) The research question of interest - Make sure when writing that someone would not need to see data to have an understanding of what is being said. |
| Indicate on the horizontal axis | the variables |
| Indicate on the vertical axis | the count, proportion, or percentage |
| Two components of statistics | Inferential and Descriptive |
| Descriptive Statistics | describing what you see, talking about statistics. |
| Inferential Statistics | take a sample in order to say something about the whole. |
| Population | looks at the whole. It measures all and then makes calculations. |
| Calculations made from a population is called a | Parameter |
| Parameter comes from | Population |
| Sample | examines the few to make an inference about the whole/population. |
| Calculations from a sample become a | statistic |
| Random Variables | Things that happen randomly (ex. rolling of a dice) |
| Quantitative | - Type of variable. - Quantity, Number (ex. height, IQ) |
| Qualitative | - Type of variable. - Is a quality, words (categorical, ex eye color, zip code) |
| Discrete | -Type of qualitative variable - Are whole numbers, not all. - ex. can't have a half of person. |
| Continuous | -Type of qualitative variable - Are on a continuum, can be any value. |
| Two defining characteristics of a variable | 1) An attribute of a person or object 2) Varies across people and object |
| Two types of variables | 1) Qualitative (height = short, tall) 2) Quantitative (height = inches) |
| Two types of quantitative variables | 1) Continuous ~ any value 2) Discrete ~ whole numbers |
| Population (T3) | Entire group of people or objects (obs. units) of interest. (T3) |
| Sample (T3) | Is a (typically small) part of the population from whom or which data are gathered to learn about the population as a whole. (T3) |
| Representative (T3) | Has similar characteristics to the population. (T3) |
| Sample Size (T3) | The number of observational units in a sample. (T3) |
| One way to avoid bias? (T4) | Give every member of the population the same chance of being selected for the sample. (T4) |
| Change sampling method to ____ (T4) | Reduce bias (T4) |
| Simple Random Sampling (SRS) (T4) | A selection method. It should ensure that every possible sample (of the desired sample size)has an equal chance of being the sample ultimately selected. (T4) |
| Table of Random Digits (T4) | A table constructed so that each position is equally likely to be occupied by any one of the digits 0-9 and so that the value in any one position has no impact on the values in any other position. (T4) |
| Unbiased (T4) | A statistic is said to provide unbiased estimates of a population parameter if values of the statistic from different random samples are centered at the actual parameter value. (T4) |
| Sampling Variability (T4) | An important statistical property- refers to the fact that the values of sample statistics vary from sample to sample. (T4) |
| Precision (T4) | Of a sample statistic refers to how much the values vary from sample to sample. (T4) |
| _____ is related to sample size (T4) | Precision (T4) |
| Sample statistics from larger samples are more ____ and ____ (T4) | Sample statistics from larger samples are more precise and closer together than those from smaller samples (T4) |
| Statistics from larger random statistics provide more accurate estimates of the _____ (T4) | _____ corresponding population parameter. (T4) |
| Random Sample (T4) | A sample chosen with an impersonal mechanism such as a random digit table, a calculator, or a computer. (T4) |
| Does the size of a population affect the samples variability? (T4) | No |
| Is the sample size crucial to assessing how a sample statistic varies from sample to sample? (T4) | Yes |
| The precision of a sample statistic depends on the ____ not the ____, if the population is large relative to the sample size (10x as large) (T4) | sample size not the population |
| Using a true random sample, can you assume that it is reasonable to generalize results from the sample to the population? (T4) | Yes, it is reasonable to generalize results from the sample to the population |
| Understanding Sample, Variable, Parameter... determine all for the Elvis poll activity (T4) | Sample: those people who heard about the poll and called in their vote Variable: the response of each individual (Elvis: alive or dead) Parameter: the proportion of adult Americans who believe that Elvis is still alive. |
| Parameter has to describe a ____ (T4) | Number |
| Do larger samples produce more precise estimates? (T4) | Yes |
| What has more effect on sampling variability: population or sample size (T4) | Sample size |
Created by:
jdemott