Some of these basic tools are: **Tables, Graphs, Charts, Mode, Mean, Median, standard deviation** etc. A table is a systematic and orderly arrangement of information, facts or data using rows and column for presentation. This makes it easier for better understanding.

Some of these basic tools are: **Tables, Graphs, Charts, Mode, Mean, Median, standard deviation** etc. A table is a systematic and orderly arrangement of information, facts or data using rows and column for presentation. This makes it easier for better understanding.

A common example of automatic stabilizers is **corporate and personal income taxes that are progressively graduated**, which means that they are fixed in proportion to the income levels of the taxpayer. Other examples include transfer systems, such as unemployment insurance, welfare, stimulus checks.

Macroeconomics is **the study of whole economies**--the part of economics concerned with large-scale or general economic factors and how they interact in economies.

**When the government spends more than its total income**, such a situation is called a fiscal deficit. It is calculated by subtracting the total income from the total expenditure and is either expressed in absolute terms or as a percentage of the GDP (Gross Domestic Product).

Macroeconomics is a branch of economics that deals with **the structure, performance and behaviour of the overall economy**. It focuses on areas like inflation, economic growth rate, price levels of various goods and services, gross domestic product (GDP), national income and the unemployment rate in a particular country.

If Adam Smith is the father of economics, **John Maynard Keynes** is the founding father of macroeconomics.

**Economic models, graphs, and scientific methods** are the three most effective tools economists use.

the standard error

**The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean**. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.

**This formula is also known as Normalized Marks Calculator.**

- X
_{n}= (S_{2}/S_{1}) (X-X_{av}) + Y_{av} - X
_{n}= Normalised Score of a Candidate. - S
_{2}= Standard Deviation of raw marks of Base Session. - S
_{1}= Standard Deviation of raw marks of Candidate Session. - X = Raw marks of the candidate which is to be normalized.

The standard error of the mean:**measures the variability of the mean from sample to sample**. is less than the standard deviation of the population. measures the variability of the mean from sample to sample.

The main difference between Mean Absolute Deviation (calculated by taking the absolute value of difference around mean) and standard deviation (calculated by squaring the differences and then adding them up and finally taking the Square Root) is that **Standard Deviation gives more weightage to the extreme value and**

**Standard deviation is the spread of a group of numbers from the mean.** **The variance measures the average degree to which each point differs from the mean**. While standard deviation is the square root of the variance, variance is the average of all data points within a group.

The standard deviation **measures the spread of the data about the mean value**. It is useful in comparing sets of data which may have the same mean but a different range. For example, the mean of the following two is the same: 15, 15, 15, 14, 16 and 2, 7, 14, 22, 30. However, the second is clearly more spread out.

Quartile Deviation, Mean Deviation, Standard Deviation and Lorenz Curve. ❖**Range** is the quickest and simplest measure of dispersion.

**Range, interquartile range**, and standard deviation are the three commonly used measures of dispersion.

The t statistic is **the coefficient divided by its standard error**. The standard error is an estimate of the standard deviation of the coefficient, the amount it varies across cases. It can be thought of as a measure of the precision with which the regression coefficient is measured.

The standard deviations is defined as the square root of the variance: **std(A) = sqrt(variance(A))** .**Function std**

- 'unbiased' (default) The sum of squared errors is divided by (n - 1)
- 'uncorrected' The sum of squared errors is divided by n.
- 'biased' The sum of squared errors is divided by (n + 1)

A standard deviation (or σ) is **a measure of how dispersed the data is in relation to the mean**. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

Deviation means change or distance. But change is always followed by the word 'from'. Hence **standard deviation is a measure of change or the distance from a measure of central tendency** - which is normally the mean. Hence, standard deviation is different from a measure of central tendency.

Dated : 22-Jun-2022

Category : Education