calculate the mean height of 200 wheat plans.the height of 200 wheat plants with class value and frequency
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UNIT-5 THEORY OF SAMPLING
AND TEST OF HYPOTHESIS
Population:
The group of individuals, under study is called is called population.
Sample:
A finite subset of statistical individuals in a population is called Sample.
Sample size:
The number of individuals in a sample is called the Sample size.
Parameters and Statistics:
The statistical constants of the population are referred as Parameters and the
statistical constants of the Sample are referred as Statistics.
Standard Error :
The standard deviation of sampling distribution of a statistic is known as its
standard error and is denoted by (S.E)
Test of Significance :
It enable us to decide on the basis of the sample results if the deviation between the
observed sample statistic and the hypothetical parameter value is significant or the
deviation between two sample statistics is significant.
Null Hypothesis:
A definite statement about the population parameter which is usually a hypothesis
of no-difference and is denoted by Ho.
Alternative Hypothesis:
Any hypothesis which is complementary to the null hypothesis is called an
Alternative Hypothesis and is denoted by H1.
Errors in Sampling:
Type I and Type II errors.
Type I error : Rejection of H0 when it is true.
Type II error : Acceptance of H0 when it is false.
Two types of errors occurs in practice when we decide to accept or reject a
lot after examining a sample from it. They are Type 1 error occurs while rejecting
Ho when it is true. Type 2 error occurs while accepting Ho when it is wrong.
UNIT V THEORY OF SAMPLING
ENGINEERING MATHS III
QUSTION BOOK
2
Critical region:
A region corresponding to a statistic t in the sample space S which lead to the
rejection of Ho is called Critical region or Rejection region. Those regions which
lead to the acceptance of Ho are called Acceptance Region.
Level of Significance :
The probability α that a random value of the statistic “t” belongs to the critical
region is known as the level of significance. In otherwords the level of significance
is the size of the type I error. The levels of significance usually employed in testing
The group of individuals, under study is called is called population. Sample: A finite subset of statistical individuals in a population is called Sample. Sample size: The number of individuals in a sample is called the Sample size. Parameters and Statistics: The statistical constants of the population are referred as Parameters and the statistical constants of the Sample are referred as Statistics. Standard Error : The standard deviation of sampling distribution of a statistic is known as its standard error and is denoted by (S.E) Test of Significance : It enable us to decide on the basis of the sample results if the deviation between the observed sample statistic and the hypothetical parameter value is significant or the deviation between two sample statistics is significant. Null Hypothesis: A definite statement about the population parameter which is usually a hypothesis of no-difference and is denoted by Ho. Alternative Hypothesis: Any hypothesis which is complementary to the null hypothesis is called an Alternative Hypothesis and is denoted by H1. Errors in Sampling: Type I and Type II errors. Type I error : Rejection of H0 when it is true. Type II error : Acceptance of H0 when it is false. Two types of errors occurs in practice when we decide to accept or reject a lot after examining a sample from it. They are Type 1 error occurs while rejecting Ho when it is true. Type 2 error occurs while accepting Ho when it is wrong. UNIT V THEORY OF SAMPLING ENGINEERING MATHS III QUSTION BOOK 2 Critical region: A region corresponding to a statistic t in the sample space S which lead to the rejection of Ho is called Critical region or Rejection region. Those regions which lead to the acceptance of Ho are called Acceptance Region. Level of Significance : The probability α that a random value of the statistic “t” belongs to the critical region is known as the level of significance. In otherwords the level of significance is the size of the type I error. The levels of significance usually employed in testing