Math 147 Quiz 1 Test 1.1, 1.2 questions and answers

Quantitative Reasoning

make judgments and predictions based on numerical values and logic

Data

Information

individual

any member of the population being studied

ex : talking about mountains the individual is a mountain

descriptive statistics

description of what you see and not predicting

inferential statistics

uses methods results from a sample

parameter

Is a numerical summary of a population

statistic

is a numerical summary based on a sample

Process of statistics

identify research objective (what question do u want to answer)

Collect the information needed to answer the question

Describe the data - organize and summarize the information

Draw conclusions

Discrete

quantitative variable that has finite number of possible values or a countable number of possible values , countable means such as 0,1,2,3,4

continuous

is a quantitative variable that has an infinite number of possible values it can take on and can be measured to any desired level of accuracy

example : when u consider possibilities = continuous , if u can assume

Levels of measurements : Qualitative

-nominal(name) = no ranking or specific

-ordinal(order) = natural order is

nominal ex: hair color ( in general is no natural ranking ) = nominal

Olympic medal = ordinal (gold,silver,bronze)

Levels of measurements : Quantitative

-interval = 0.. 10-15 is an interval , on a number line distance between two points is interval - ratio doesn't make sense but distance between value does

-ratio = if ur guessing choose ratio , only some exceptions for interval (most common)

explanatory

x axis

response

y axis

observational study

don't attempt to manipulate explanatory variable , look at the two and see if there's a pattern

do not allows researcher to claim causation, only association

Compounding

occurs when the effects of two or more explanatory variables are not separated

Confounding

tryin to isolate and there's a variable that are effecting both

Lurking variable

Is an explanatory variable that was not considered in a study

To show one variable causes a change in a second variable

we need to do a designed experiment

Cross sectional studies

observational studies that collect information about individuals at a specific point in time , or over a very short period of time

Case-control studies

these studies are retrospective , meaning that they require individuals to look back in time or require the researcher to look at existing records. In case control studies individuals who have certain characteristics are matched with those that do not.(records from the past)

Cohort(group of people) studies

long period of time , look for patterns

Longitudinal study

cohort.. almost the same thing , journalist prefer longitudinal wording

Census

population

survey

sample

designed experiment

intentionally manipulate the values of the explanatory variable

random sampling

is the process of using chance to select individuals from a population to be included in the sample

n

sample size

N

population size

frame

a list of every individual in the population, populations keeps changing so its hard to have an exact frame

obtain simple random sample

list of all individuals in the population (frame)

number the population list either sequentially or randomly

choose a sample size n

generate n random numbers and choose those values from your numbered frame

Stratified sampling

obtained by separating the population into homogenous(the same) nonoverlapping groups called strata, and then obtaining a simple random sample from each stratum. The individuals within each stratum should be homogenous in some way

Systematics sampling

choose every k^th from the population . The first individual selected is a random number between 1 and k ( doesn't require frame )

Cluster

obtained by selecting all individuals within a randomly selected collection or group of individuals

Convenience sample

is one in which the individuals in the sample are easily obtained (facebook)

biased in sampling

trying to obtain info through the sampling process and anything involved in the sampling process that distorts that information is called

sampling bias

means the technique used to obtain the individuals to be in the sample tends to favor one part of the population over another

under coverage

occurs when the proportion of one segment of the population is lower in a sample than it is in the population, like there are more women than men for ex

no response bias

exists when individuals selected to be in the sample who do not respond to the survey have different opinions from those do

non response can be improved through

the use of callbacks or rewards/incentives

response bias exists when

the answers on a survey do not reflect the true feelings of the respondent

types of response bias

-Interviewer error

-Misrepresented answers

-Words used in the survey question

-Order of the questions or words within the question

sampling errors

does not involve a mistake, is an error that results from using a sample to estimate information about a population. This type of error occurs because a sample gives incomplete information about a population

Confirmation bias

researchers have a tendency, both consciously and unconsciously to only see evidence that confirms their own preconceptions

experiment is a

controlled study conducted to determine the effect of the response variable of varying one or more explanatory variables or factors

treatment

any combination of the values of the factors

the experiment unit or subject is

a person object or some other well defined item upon which a treatment is applied

A control group serves as a

baseline treatment that can be used to compare to other treatments

a placebo is an

innocuous medication, such as a sugar tablet , that looks , tastes and smells like the experimental medication

blinding refers to

nondisclosure of the treatment an experimental unit is receiving

a single blind experiment is one in which

the experimental unit does not know which treatment he or she is receiving

a double blind experiment is one

in which neither the experimental unit nor the researcher in contact with the experimental unit knows which treatment the experimental unit is receiving

To design an experiment means explaining the plan

identify the problem

Determine the factors that affect the response variable

Determine the sample Size

Control and randomize

Conduct experiment

Test the claim

Inferential statistics you

take sample results and extend them to the population

Completely randomized design

means you put experimental units is randomly assigned to a treatment level

Matched-pairs design is an

experimental design in which the experimental units are paired up. The pairs are matched up so that they are some how related . There are only two levels of treatment in a matched pairs designed