Statistical Hypothesis: [ Ссылка ]
Central Limit Theorem: [ Ссылка ]
Descriptive Statistics: [ Ссылка ]

[ Ссылка ]

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Complete Exercise
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[ Ссылка ]
Reject H0 if : 〖𝑼= 𝐦𝐢𝐧⁡(𝑼〗_𝟏, 𝑼_𝟐) is less than Critical value.
See U table given at the above link.
Notice, you must find entry that corresponds to both n1 and n2.



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Approximating binomial distribution with normal
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#observations in each sample; also the number of coins tossed
n_obs=30

#sample size
s_size=100

adjustment = 1e+2 #1e+3, depends on the height of histogram. If values touch thousands, then it should be 1e+3, otherwise adjust accordingly

fbindat=rbinom(s_size,n_obs,.5)

#plot
hist(fbindat,breaks=seq(0,n_obs,1), xlab ="Positive Signs", main=paste("Bin(",n_obs,",0.5)"))

#Check with theorectical curve
lines(seq(0,n_obs,1),dbinom(seq(0,n_obs,1),n_obs,0.5)* adjustment ,col="blue")



Introduction:
--------------------
This is a series of videos that produces a university course on Applied Statistics.

The link to video series is: [ Ссылка ]_

The topics covered are:

Aggregating information; measures of central tendency.
Spread of information; data distributions.
Collecting information; surveying and sampling.
Testing beliefs; hypothesis testing.
Associating different pieces of information; correlations.
Predicting outcomes; regression.

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