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Mathematics 18 Online
OpenStudy (anonymous):

HELP PLEASEEEE (algebra 2)

OpenStudy (anonymous):

You test 8 automobiles and find that their mileage ratings are 25, 25, 26, 27, 30, 31, 32, and 340 mpg, arranged in order from smallest to largest. The average of these numbers is 536 ÷ 8, or 67 mpg. However, the last data value (340 mpg) seems impossibly large, and you decide that it must be due to an error in the data gathering process. Rather than doing all your measurements all over again, at considerable expense, you decide to simply ignore the "bad" value of 340 mpg. (When they do this, scientists say they are "rejecting the outliers," by ignoring unreasonable values that are nowhere close to the main cluster of data points. This procedure has some risks.) What is the mean of the remaining mileage numbers? HUH???

OpenStudy (nubeer):

lmao.. alot of sentences just to confuse.. just ignore the 340.. and find the mean of the rest mean = sum of all/ no. of samplees

OpenStudy (anonymous):

why ignore 340?

OpenStudy (nubeer):

because it is said in the question.

OpenStudy (anonymous):

and do i add numbers that are there more than once? like 25 and 25?

jimthompson5910 (jim_thompson5910):

if you include 340, the mean is 67, which is clearly much larger than 30, 31, 32, but if you drop 340, then finding the mean of 30, 31, 32 will give you a number that's much closer to 30, 31, 32

jimthompson5910 (jim_thompson5910):

sorry I meant to say "25, 25, 26, 27, 30, 31, 32" instead of just "30, 31, 32"

OpenStudy (nubeer):

yeah you have to add them twice

OpenStudy (anonymous):

so the answer is 28??

jimthompson5910 (jim_thompson5910):

that is correct

OpenStudy (nubeer):

yeah

OpenStudy (anonymous):

A production manager tests 10 toothbrushes and finds that their mean lifetime is 450 hours. She then designs a sales package for this type of bulb stating that consumers can expect it to last approximately 460 hours. This is an example of what phase of inferential statistics?

OpenStudy (anonymous):

A. Data gathering B. Data analysis C. Probability-based inference D. Data organization

OpenStudy (anonymous):

???

OpenStudy (nubeer):

i guess C but not sure.

OpenStudy (anonymous):

thanks, anyone else that is sure?

jimthompson5910 (jim_thompson5910):

yes I agree inference is making assumptions or educated guesses based on the gathered and analyzed data, so she's guessing that the toothbrushes will last 460 hours

OpenStudy (anonymous):

thanks! you guys are soo smart

OpenStudy (anonymous):

Which of the following activities are examples of data organization and analysis? Check all that apply. A. Running a weather station B. Rejecting extreme data C. Transferring the weather data to a computer application D. Summing the number of days with precipitation, summing the number of sunny days, and summing the number of cloudy days without precipitation E. Drawing a pie chart to show the percentage of sunny days, rainy days, and cloudy days without precipitation

OpenStudy (anonymous):

C, D, E?

OpenStudy (nubeer):

i think E..

OpenStudy (anonymous):

just E? it could be more than one

jimthompson5910 (jim_thompson5910):

in C, you're just doing organization and not much analysis

OpenStudy (anonymous):

oh.. it was D and E

OpenStudy (nubeer):

lol if u think we are smart you should be writing testimonials for both of us later on :P :P

OpenStudy (nubeer):

lol well then D and E,, ddn't knew can pick more thn one option

OpenStudy (anonymous):

huh?

OpenStudy (anonymous):

Shortly before the 1932 presidential election, a national magazine conducted a telephone survey of voters. Based on the results of the survey, the magazine predicted that Herbert Hoover (Republican) would beat Franklin Roosevelt (Democrat) by a landslide. In fact, exactly the opposite happened. The trouble with the survey was that in those Depression days, only rich people could afford phones, and they were likely to vote Republican. This is a classic example of an error in which phase of inferential statistics?

OpenStudy (anonymous):

sorry i keep asking more.. but seems like you guys really know this stuff.. and im home schooled and am really lost with this.. thats why i came on here. and i have a lott of quizzes and a test to do still by tomorrow..

OpenStudy (nubeer):

any options with this one??

OpenStudy (anonymous):

oh ya! sorry

OpenStudy (anonymous):

A. Data organization B. Data analysis C. Data gathering D. Probability-based inference

jimthompson5910 (jim_thompson5910):

hint: it has to do with drawing up the samples

OpenStudy (anonymous):

D?

jimthompson5910 (jim_thompson5910):

that's one of the last steps, making decisions based on what you drew up

jimthompson5910 (jim_thompson5910):

but what they want is one of the first steps

OpenStudy (anonymous):

ohh A?

jimthompson5910 (jim_thompson5910):

that's also towards the end too, so that's out

OpenStudy (anonymous):

or C

jimthompson5910 (jim_thompson5910):

you start by gathering your data first

jimthompson5910 (jim_thompson5910):

you need data to organize it and make analysis and inference off it

OpenStudy (anonymous):

got it!! so: When the production manager finds the average life of her toothbrush-lifetime data, this is an example of what phase of inferential statistics? A. Probability-based inference B. Data organization C. Data analysis D. Data gathering A or C?

jimthompson5910 (jim_thompson5910):

A is making a guess based off what you find in C

OpenStudy (anonymous):

ohh D?

jimthompson5910 (jim_thompson5910):

step 1) design a study step 2) gather the data step 3) analyze the data step 4) organize the results and make them presentable step 5) make guesses or inferences based on the results

jimthompson5910 (jim_thompson5910):

that's your basic outline for any statistical study

OpenStudy (anonymous):

so D?

jimthompson5910 (jim_thompson5910):

no it's not gathering

jimthompson5910 (jim_thompson5910):

you analyze the data after you gather it

OpenStudy (anonymous):

huh?? i dont get what its asking..

jimthompson5910 (jim_thompson5910):

when you have a bunch of numbers and you average them, what are you doing to that data? gathering it? or analyzing it?

OpenStudy (anonymous):

analyzing

jimthompson5910 (jim_thompson5910):

correct

jimthompson5910 (jim_thompson5910):

so you're at the data analysis stage

OpenStudy (anonymous):

ohh so C

jimthompson5910 (jim_thompson5910):

yes

OpenStudy (anonymous):

You test 8 automobiles of the same make and model and find their mileage ratings to be 25, 25, 26, 27, 30, 31, 32, and 1,000,000 mpg, arranged in order from smallest to largest. If you use inferential statistics (and reject the outlier) to predict what mileage consumers can expect when they buy this type of car, what value will you predict? A. 125,024.5 mpg B. 28 mpg C. 67 mpg D. 24.5 mpg E. 30 mpg looking for what? mean, mode, median...?

jimthompson5910 (jim_thompson5910):

sounds like you want the mean

OpenStudy (anonymous):

of 25, 25, 26, 27, 30, 31, and 32?

jimthompson5910 (jim_thompson5910):

yes

jimthompson5910 (jim_thompson5910):

the outlier really really skews the mean, so ignore it completely since it's just one value and it doesn't represent the majority

OpenStudy (anonymous):

When the production manager arranges her data on product lifetimes from the smallest to the largest number, this is an example of what phase of inferential statistics? A. Data gathering B. Data collection C. Data organization and analysis D. Probability-based inference C?

jimthompson5910 (jim_thompson5910):

yeah I think so, you're organizing or arranging the data

OpenStudy (anonymous):

thankss

jimthompson5910 (jim_thompson5910):

np

OpenStudy (anonymous):

OpenStudy (anonymous):

???????

jimthompson5910 (jim_thompson5910):

basically the first bar represents how many numbers start with 3 so numbers like 342, 375, etc

jimthompson5910 (jim_thompson5910):

the next bar represents numbers that start with 4 (like 412, 423, etc) and so on

OpenStudy (anonymous):

/D

OpenStudy (anonymous):

??

jimthompson5910 (jim_thompson5910):

good

OpenStudy (anonymous):

choices in next pic

OpenStudy (anonymous):

*check more than one*

OpenStudy (anonymous):

???????????

jimthompson5910 (jim_thompson5910):

any ideas?

OpenStudy (anonymous):

D. a or b

OpenStudy (anonymous):

or all 4.? A,B,C,D

jimthompson5910 (jim_thompson5910):

E is definitely false

jimthompson5910 (jim_thompson5910):

but are you sure about B? look again

OpenStudy (anonymous):

oh. read it wrong. exhausted and overwhelmed! :(

OpenStudy (anonymous):

so A, C, D?

OpenStudy (anonymous):

nvm got that one! i have more tho

jimthompson5910 (jim_thompson5910):

ok just one more

OpenStudy (anonymous):

can be more than one!

OpenStudy (anonymous):

????????

OpenStudy (anonymous):

hello?

jimthompson5910 (jim_thompson5910):

hint: the area under the curve represents probability you can't have a negative probability

jimthompson5910 (jim_thompson5910):

areas above the x axis represent positive areas areas below the x axis represent negative areas

OpenStudy (anonymous):

huhh

OpenStudy (anonymous):

soo.....????

jimthompson5910 (jim_thompson5910):

for instance, this function has a positive area |dw:1379482912285:dw| but this function has a negative area |dw:1379482935885:dw|

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