Question

Respond to the following in a minimum of 175 words:

Explain the following two topics from our course readings and provide an example of each:

a: Hypothesis testing

b: Regression analysis

Answer 1

typothesis Testing - A statistical hy bothesis is Some statement or Assertion about a population or equuiolently about the probability distribution charaterising a population which we want to verify on the basis of information available m a sample. If the Sefertistical hypothesis specifies the population completely then it is simple hypothesis otherwise it is called composite statistical Hypothesis example if X, st. - xn is a rendery sample of szen from e normal population with mean in a variance then Hypothesis M=4o, Pat? is a simple Hypothesis A Hypothesis which does not completely sfrecify is parameters of a population is composite hypothesis with or degree of freedomy I (He) Null Hy no thesis A decisim-maker should not be motivated by prospects of profit or loss resulting from the acceptance of rejection of Hypothesis. He should be completely impartial .. example Drug A nanufacut red by 1st concern and Drug B by and concern. Each company claims that its drug is superior to that of other and desired of test. Letx denotes the adelitional hours of sleep effect by drug A and y be drug B. Here our Null Hypothesis is that no difference between effects of two drugs Ho: M = My M, My are probability distributing with mean.

Alternative Hypothesis in Being tested because the acceptance or rejection of hull hy hothesis is meaningful only it is being tested against a rival hypothesis which ald rather be explicitly mentioned Represent Alternative Hypothesis by Hi for example. In example of Drugs, Hi! My My us H,: Myrtly on Hi: Mx Fly one failed tests two tail tests, (6.) Regression Analysis: > is a mathmatical measure of average relationship between two of more variables in terms of coiginal units of clata, In Regression Anaalysis there are two types of variables: ☺ Dependent variable or Regressed wastable © Independent variable as Regressor ur predictor verlable. Dependent variable whose value is influenced or do be predicted, Independent verable the values or is which used for influences prediction

Line of Regression of is the line which gives best estimate to the value of one variable for any specific value of other vastables. This line of regression is the line of "Best fit" and is obtained by "Principle of least squares" Line of Regression of y ou x and since line of regression passes through (r , g), its equation a y-ý=bCx-5) Yo ý = & Jy (x-2) for example no Linear regression can be used to quantify the impact of Industry, Traffic on Air pollution. © linear regressim can be used in agriculture to quantify the Impact of seeds, fertilizers, Pesticides on the crop Producation,