Statistics Homework Help




Statistics is a branch of applied mathematics that involves the collection, description, analysis, and inference of conclusions from quantitative data. The mathematical theories behind statistics rely heavily on differential and integral calculus, linear algebra, and probability theory. Statisticians, people who do statistics, are particularly concerned with determining how to draw reliable conclusions about large groups and general phenomena from the observable characteristics of small samples that represent only a small portion of the large group or a limited number of instances of a general phenomenon.

Statistics are used in virtually all scientific disciplines such as the physical and social sciences, as well as in business, the humanities, government, and manufacturing. Statistics is fundamentally a branch of applied mathematics that developed from the application of mathematical tools including calculus and linear algebra to probability theory.

In practice, statistics is the idea we can learn about the properties of large sets of objects or events (a population) by studying the characteristics of a smaller number of similar objects or events (a sample). Because in many cases gathering comprehensive data about an entire population is too costly, difficult, or flat out impossible, statistics start with a sample that can conveniently or affordably be observed.

The two major areas of statistics are known as descriptive statistics, which describes the properties of sample and population data, and inferential statistics, which uses those properties to test hypotheses and draw conclusions. Statisticians measure and gather data about the individuals or elements of a sample, then analyse this data to generate descriptive statistics. They can then use these observed characteristics of the sample data, which are properly called “statistics,” to make inferences or educated guesses about the unmeasured (or unmeasured) characteristics of the broader population, known as the parameters.

Some common statistical tools and procedures include the following:

  • Descriptive
  • Mean (average)
  • Variance
  • Skewness
  • Kurtosis
  • Inferential
  • Liner regression analysis
  • Analysis of variance (ANOVA)
  • Logit/Probit models
  • Null hypothesis testing


  • Statistics is the study and manipulation of data, including ways to gather, review, analyze, and draw conclusions from data.
  • The two major areas of statistics are descriptive and inferential statistics.
  • Statistics can be used to make better-informed business and investing decisions.

Two types of statistical methods are used in analysing data: descriptive statistics and inferential statistics.

Descriptive Statistics

Descriptive statistics mostly focus on the central tendency, variability, and distribution of sample data. Central tendency means the estimate of the characteristics, a typical element of a sample or population, and includes descriptive statistics such as mean, median, and mode. Variability refers to a set of statistics that show how much difference there is among the elements of a sample or population along the characteristics measured, and includes metrics such as range, variance, and standard deviation.

Inferential Statistics

Inferential statistics are tools that statisticians use to draw conclusions about the characteristics of a population from the characteristics of a sample and to decide how certain they can be of the reliability of those conclusions. Inferential statistics are used to make generalizations about large groups, such as estimating average demand for a product by surveying a sample of consumers’ buying habits or to attempt to predict future events, such as projecting the future return of a security or asset class based on returns in a sample period.

Who uses statistics?

Statistics are used widely across an array of applications and professions. Any time data are collected and analysed, statistics are being done. This can range from government agencies to academic research to analysing investments.

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