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Lecture 1

# STAT 2606 Lecture Notes - Lecture 1: Statistical Inference, Scatter Plot, Pareto Chart

2 pages108 viewsFall 2018

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**preview**shows half of the first page. to view the full**2 pages of the document.**STAT2606 - Basics of Statistics

Definitions:

Measures of location: Tools such as finding the mean or median.

Mean: The mean is the average of all the numbers in a set, it can be found by adding all the numbers in a

set, then dividing it by the number of numbers in the set.

Median: The median is used to measure the centre of values, it can be found by ordering a set of values

from smallest to largest in value, the middle value is the median if it is an odd amount of numbers in the

set. However, if it is an even amount of numbers take the two middle values and take the average of the

two by adding them together then dividing that number by two.

Measures of spread: Tools like variance, standard deviation, and range.

Variance:

The variance measures the difference between the mean and each number in a set.

Step one, find the mean.

Step two, subtract the mean from each number in the set.

Step three, square each of the results from step two.

Step four, find the averages of the squared values from step three.

Standard deviation:

Standard deviation, denoted σ, measures how dispersed a set of values are from each other.

To find the standard deviation square root the variance.

Range:

For inferential statistics, the range is the difference between the biggest and smallest numbers in a set.

For descriptive statistics, the range is the difference between the biggest and smallest numbers in the

smallest interval.

Pareto charts:

A Pareto chart uses both a bar and line graph. The values are shown in descending order by bars, and the

collective total is denoted by the line.

Histograms:

A histogram looks like a bar graph but instead of displaying the relationship between two variables a

histogram shows the probability distribution of one continuous variable.

Population: A population is tested usually when the population is a specific small group that can be tested

easily. A population can be defined as the entire group. Example: all students attending university in

Canada.

Sample: A sample is used when a population may be too large to measure or test without taking too much

time. A sample is a portion of the population. Example: ten students attending each university in Canada.

Simple Random Sampling: A sample that is made with all things in the population having equal chance of

getting picked. Example: Picking names out of a hat.

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