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Let's start with the fundamentals of statistics.
What Is Statistics?
Statistics is a science subset that majors in numerical data collection, analysis, interpretation, and presentation. It's a broad subject that can be grouped differently in terms of:
- Quantitative classification
- Qualitative classification
- Geographical classification
- Chronological classification
Statistics is mainly divided into two:
- Descriptive statistics: Describes the characteristics, features, and behavior of a given data set. It involved everything from data collection, analysis, and presentation. But not drawing inferences.
- Inferential statistics: Complements descriptive statistics because it majors on drawing inferences and making decisions from the already available and organized data.
The knowledge of statistics prepares you for a rewarding career as a statistician. So come to use with any statistical concepts or statistics assignment, and we'll gladly help you understand and score high grades in statstics.
Before we tell you how our statistics homework help service works and ensure you get high grades, there is a need to delve into statistical types and their various components.
Types of Differential Statistics
Measures of Frequency
Measures of frequency denote how often a certain element within a data set occurs. The main concepts in measures of frequency are:
- Frequency--the actual number of times a datum occurs in a data set
- Relative Frequency--The normal frequency as a proportion of the entire data set
- Cumulative Frequency--A summation of relative frequency or normal frequency
Since these are just the basics of statistics, all our statistics assignment writers are well-conversant with them, so you can be sure of a quality solution that helps you score good grades.
Measures of Central Tendency
Measures of central tendency focus on how close a given datum/element is to the middle (central) value. The three popular measures of central tendency are:
- Mean
- Median
- Mode
You are asked to calculate the three measures from the same data set in almost every statistics assignment. And again, these are simple but challenging when dealing with grouped data. So if you feel you need some clarifications, proceed to consult online statistics assignment help platforms for help.
Measures of Dispersion (Variation)
In statistics, measures of dispersion show how data spreads from the middle value. The key measures of dispersion that you will never miss in your statistics homework include:
- Range
- Quartile and Interquartile Range
- Deviation
- Standard deviation
- Kurtosis
- Skewness
Regardless of the complexity, the approach is simple when using individual formulas. Our online statistics assignment experts team will help you complete the homework on time, produce a quality assignment, and help you get high grades.
Measures of Position
Measures of position describe the position of a single element compared to the other elements in a data set. They are expressed as:
- Percentiles (Out of 100)
- Deciles (Out of 10)
- Quartiles (Out of 4)
- Standard scores (z-scores)
Types of Inferential Statistics
- Analysis of Variance (ANOVA): In an Analysis of Variance assignment, you are expected to use different estimation procedures to calculate how different arithmetic means differ.
- Confidence Intervals (CIs): Most college students confuse confidence intervals for mode. However, the concept applies in grouped data--the bounds within which there is the highest probability of finding a given value.
- Hypothesis Testing: We specify two complimentary statements and use the available data to prove which statement holds.
- Regression analysis: Regression analysis focuses on finding a relational function that associates dependent and independent variables. From the function/equation, students can find the values of the dependent variable by substituting different values of the independent variable(s).
Other Common Topics We Encounter in Our Statistics Homework Help Service
- Probability distributions
- Statistical Software System (SAS)
- Random Variables
- R Programming
- Sampling Theory
- Linear Programming
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