### Some Basic Stat Concepts from my notes

• Correlation
• Pearson: Product Corelation
• Spearman: Rank Corelation
• Whenever we have Ordinal Data (Rank Column, Marks of Students ).
• If two ranks are same, then (next rank+(next+1))/2 rank, i:e (2+3)/2
• If Three ranks are same, then rank is: (next rank+(next+1)+(next+2))/2. i: 1+3+4/2
• And so on.
• Hypothesis Test
• Find t value
• Find p value
• Check it p value less than  or more than alpha
• If p value is less than alpha then
• T Test: Sample Size is Small: Say 30.
• One Tail Test
• When Hypothesis talks about mean as > or < of Certail value
• When Fail to reject Null Hypothesis?
• If the P from test is > than Alpha(0.05, generally), then Null Hypothesis is Accepted(Failed to reject)
• If T from experiment is < than T found out for Degree of Freedom(Number of Observations) and Critical Value (Alpha say 0.05) from T Table of One Tail, then Null Hypothesis is Accepted.
• Two Tail Test
• When Null Hypothesis talks about = of certain value.
• When Fail to reject Null Hypothesis?
• If the P from test is > than Alpha(0.05, generally), then Null Hypothesis is Accepted!(Failed to reject)
• If T from experiment is beyond T Area(Experiment T must not fall in between Table T value range( found out for Degree of Freedom(Number of Observations) and Critical Value (Alpha say 0.05) from T Table of One Tail, then Null Hypothesis is Accepted.
• Normal Distribution
• 68-95-99.7 for 1,2,3 SD Area from Mean.
• Standardization:
• z(i)=(x-mean)/(standard distribution)
• Skewness is a measure of symmetry, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the center point.
• Kurtosisis a measure of whether the data are peaked or flat relative to a normal distribution.
• Mean Absolute Deviation: x-Mean
• Upper Hinge: Mid of Median to Max Value
• Lower Hinge: Mid of Median to Min Value

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