#1 I post this post twice I need 2 different views, please don\'t copy your answ

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#1

I post this post twice I need 2 different views, please don't copy your answers to both of my posts. Please answer all. Please answer these questions briefly, thanks

1.What is meant by statistics?

2.We use statistics to generate information for decision making from data. We also use either descriptive statistics or inferential statistics. Can you explain their applications and the type of data?

3.There are two basic types of variables, can you name them and provide examples.

4.Data can be classified according to levels of measurement. The level of measurement determines how data should be summarized and presented. There are four levels of measurement, can you name them and provide examples for each level.

5.What do we mean by mutually exclusive categories and provide examples?

6.What are the differences between interval level of measurements and ratio level of measurements?

Explanation / Answer

1.

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

Also, properties of samples, such as the mean or standard deviation, are called statistics.

2.

Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analysed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data.

Descriptive statistics are applied to populations, and the properties of populations, like the mean or standard deviation, are called parameters as they represent the whole population (i.e., everybody you are interested in).

Inferential statistics are techniques that allow us to use these samples to make generalizations about the populations from which the samples were drawn.

3.

Categorical variable: Variables than can be put into categories. For example, the category “Type of Bird” might contain the variables "Peacock" and "Penguin".

Quantitative variable: A broad category that includes any variable that can be counted, or has a numerical value associated with it. Examples of variables that fall into this category can be the number of students in a class.

4.

A variable has one of four different levels of measurement:

i. Nominal :

The nominal type differentiates between items or subjects based only on their names or (meta-)categories and other qualitative classifications they belong to; thus dichotomous data involves the construction of classifications as well as the classification of items. Discovery of an exception to a classification can be viewed as progress. Numbers may be used to represent the variables but the numbers do not have numerical value or relationship: for example, a globally unique identifier. Examples of these classifications include gender, nationality, ethnicity, language, genre, style, biological species, and form.

ii. Ordinal :

The ordinal type allows for rank order (1st, 2nd, 3rd, etc.) by which data can be sorted, but still does not allow for relative degree of difference between them. Examples include, on one hand, dichotomous data with dichotomous (or dichotomized) values such as 'sick' vs. 'healthy' when measuring health, 'guilty' vs. 'not-guilty' when making judgments in courts, 'wrong/false' vs. 'right/true' when measuring truth value, and, on the other hand, non-dichotomous data consisting of a spectrum of values, such as 'completely agree', 'mostly agree', 'mostly disagree', 'completely disagree' when measuring opinion.

iii. Interval :

The interval type allows for the degree of difference between items, but not the ratio between them. Examples include temperature with the Celsius scale, which has two defined points (the freezing and boiling point of water at specific conditions) and then separated into 100 intervals, date when measured from an arbitrary epoch (such as AD), percentagesuch as a percentage return on a stock,[16]location in Cartesian coordinates, and direction measured in degrees from true or magnetic north.

iv. Ratio :

The ratio type takes its name from the fact that measurement is the estimation of the ratio between a magnitude of a continuous quantity and a unit magnitude of the same kind. A ratio scale possesses a meaningful (unique and non-arbitrary) zero value. Most measurement in the physical sciences and engineering is done on ratio scales. Examples include mass, length, duration, plane angle, energy and electric charge.

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