Inferential statistics

Question 1

بسم الله الرحمن الرحيم
________________
population measures and smaple measures

Answer 1

population :
u For mean - sigma for SD - sigma square FOR variance - and pi for proprtion
_______________
sample
X for mean
S2 for vairane
S for SD
Proptrion =p

Question 2

The process of drawing conclsions from data obtained from the sample to the population form which it was selected?

Answer 2

Statistical inferences

Question 3

Statistical inference imp in ?

Answer 3

Paramater estimation
Hypothesis testing

Question 4

how to get SD?

Answer 4

To get the mean then
The value - mean then square the result and divde it on( n-1)
so you got variane get the root

Question 5

SE=

Answer 5

SD/Root of N of sample

Question 6

Unkownpopulation parameter =

Answer 6

Sample statistic +- Sampling error

Question 7

The difference between a sample statitistic used to estimate a population parameter and the actual but unkonwon value of the parameter

Answer 7

It is ?
Sampling RANDOM error

Question 8

As the sample size increases the stadnaed error ?

Answer 8

decreased!

Question 9

population proprtion =

Answer 9

sample proportion p +- rendom error
=p +- z X SE proption
=p +- z X root of (P(1-P)/N)

Question 10

We have 1000 person scanned for DM :
25 diabetics
so :
The proption of sample
The SD of proption
The SE = ?
get 95 % confidence interval

Answer 10

The proprtion of sample= 25/100= 0,25
SD = Root of ( p(1-p))
= root of ( .25 x ,75 )
=0.43
SE Proptortion = SD/Root of N =
=0,043
95 % CONFIDENCE INTERVAL = 0.25+- ( 1,96 X 0,043)=(17,1 - 32.8)

Question 11

Central limit therorem
If we have a variable as SBP
- that is normally distributed in a population with
- mean u
-standard deivation sigma
-and we have many samples of the same size of N THEN

Answer 11

The means of these samples will be normally distributed with mean= u of population
and Standard devtiation = sigma / root of N

Question 12

Unknwon population parameter = sample statistics +- sample error
but
Population parameter =

Answer 12

Sample statistics +-( Z*sampling error )
Z= Confidence cofficent which is constant

Question 13

The best point of estimate for Population parameter is ?

Answer 13

the one you deduce from Random representational sample but without Certtainity
sample 64
Mean of SBP =129
SD = 4
so you can say without certainity the population mean bp= 129
if you want certainity use? Confidence Interval

Question 14

Z 95% = ?

Answer 14

1,96

Question 15

Z90% =

Answer 15

1.64

Question 16

Z99% Confidence coffienet = ?

Answer 16

2,58

Question 17

sigma =

Answer 17

root of
(Value -mean)square /N

Question 18

SE=

Answer 18

SD/root of N

Question 19

If a 64 PERSON sample with SD= 4 calculate the SE?
if the mean BP = 129
then calulcate Confidence interval and intepret the result

Answer 19

SE =4/Root 64
=4/8
=1/2
CI=
129+- 1.96*,5
128.02:129,98
_____________
YOU ARE KNOW SURE 95% that population means lie in the range between ,,,m,,,,

Question 20

A reange of values between Lower Confidence Linit and Upper Conifence limit that the population parameter lies within this range with a certain degree of Confidence called confidence level usually 95%

Answer 20

Confidence Interval

Question 21

As the Z value becomes larger

Answer 21

The range of Confidence interval becomes larges

Question 22

As the range of confidence interval become lesser

Answer 22

The More it beomces percise

Question 23

What is the result of increasing sample in confidence interval give reason ?

Answer 23

Decreasing the range of confidence interval so becomes more percise
______________________
The SE= sd / root of N
N increased so SE decreased and in consequncse
the Z*SE decrreases so the range decrease

Question 24

Can be used to inference pipulation parameter

Answer 24

Each static form of sample
SD RR OR mean

Question 25

ولما جاءت رسلنا إبراهيم بالبشري قالوا سلاما

Question 26

standard deviation of sampling distribution

Answer 26

Standar erroe

Question 27

Mean SE
Proportion SE?

Answer 27

MEAN SE=Sd/root N
Proporiton SE= ROOT
(P(1-P)/N)