Mean & Std. Deviation symbols for Sample and Population

When do we use Non-Parametric Statistics or What are the problems for which Non-Parametric statistics is used:-

1) Differences between Independent Groups
2) Differences between Dependant groups
3) Relationship between Variables
4) Descriptive Statistics
5) Problems and Non-Parametric Tests:

A) 2 or more independent groups
B) Paired Observations
C) Randomised Blocks
D) Rank Correlation

The Normal Distribution and the 68-95-99.7 Rule

👆Formulae for Standard Deviation, Variance and Covariance.

Mode, Median, Mean, Range, and Standard Deviation

Wilcoxon Signed Rank Test for a paired sample [Problem 1 with Solution] - Hypothesis Testing

Analogue. In psychological research an analogue experiment is a structured experiment that compares the events of two situations in order to look for correlations. ... These types of experiments can result in either a positive or negative correlation.

The level of Significance refers to the degree of Significance with which we accept or reject a particular hypothesis.

Since 100% accuracy is not possible in taking a decision over the acceptance or rejection of a hypothesis, we have to take a particular level of confidence fixed either at 5% or 1% etc..

In simple terms, The level of Significance is the probability of rejecting the null hypothesis when it is true.
For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference.

Statistical Inference types

Statistical Inference is concerned with using probability concept to deal with uncertainty in decision making.

It refers to the process of selecting and using a sample statistic to draw inference about a population parameter based on a subset of it, i.e the sample drawn from the population.

Statistical Inference treats 2 different classes of Problems:
A) Hypothesis testing
B) Estimation

Statistical Estimation is concerned with the methods by which population characteristics are estimated from sample information.

Basic characteristics of Estimators are
1) Unbiasedness and Minimum Variance
2) Consistency
3) Efficiency
4) Sufficiency

A Point Estimate is a single number computed from the sample values x1, x2,..... xn which is used as an estimate of the unknown population parameter.

An Interval Estimate would always be specified by 2 values i.e the lower one and upper one.

Interval Estimation refers to the Estimation of a population parameter by a random Interval called the confidence Interval whose end points L and U called the confidence limits and are random end points of interval estimate.

Point Estimation has an advantage as much as it provides an exact value for the parameter under investigation.

Mode Formula in Statistics

Statistics Psychology Syllabus

Sampling Error formula

Standard Error Formula in Statistics

t-Test ( formula no.3 )