Lecture 1: Introduction to Statistics & Introduction to Excel ⢠A ...
Lecture 1: Introduction to Statistics & Introduction to Excel
A population consist of all the members of a group about which you want to draw a conclusion A sample is the portion of the population selected for analysis A parameter is a numerical measure that describes a characteristic of a population A statistic is a numerical measure that describes a characteristics of a sample
Population and Sample data
Greek letters are used for population data (μ, σ, Ν) Roman letters are used for sample data (x, s, n) A sample is a selection of measurements (subset) from all measurements (population)
Descriptive statistics o Collect data *survey* Important sources *survey, study, data distributed by organisation or a individual* Data sources classified as Primary sources Secondary sources o Present data *tables and graphs*
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n * o Characterise data * sample mean Inferential statistics o Drawing conclusions about a population of data based on the sample data o Estimation *estimate the population mean weight (parameter) using the sample mean weight (statistic)* o Hypothesis testing *testing the claim of a population*
Types of data
Categorical data vs. numerical data o Numerical data (quantitative) is measure on a natural numerical scale Age/share price/number of people in the lecture room/results of 123 Continuous or discrete Continuous – data that can be any real number. Example time to travel to work 54.234 minutes Discrete – countable number or responses, example numbers of students in a lecture room. Can you have half a student? o Categorical data (qualitative) can only be named or categorised Gender/satisfaction very good, good, average, poor Nominal or ordinal Nominal – no natural or implied order No response is considered better Ordinal – there is an implied order Definite order
DATA
(Qualitative)
Numeric al (Quantitative)
Time series or cross sectional o Time series – data collected through time o Cross sectional – data collected for a point in time
Week 1 Quiz 1) The collection and summarisation of the socioeconomic and physical characteristics of the employees of a particular firm is an example of a. Descriptive statistics b. Inferential statistics c. A parameter d. A statistic 2) The estimation of the population average family expenditure of food based on the sample average expenditure of 1,000 families in an example of a. A parameter b. Descriptive statistic c. Inferential statistics d. A statistic 3) The portion of the universe that has been selected for analysis is called a. A statistic b. A parameter c. A frame d. A sample 4) A summary measure that is computed to describe a characteristic of an entire population is called a. A statistic b. The scientific method c. A parameter d. A census 5) Which of the following is most likely a population as opposed to a sample a. Registered users in a stat b. The first 5 students completing an assignment c. Every third person to arrive at the bank d. Responds to a newspaper survey 6) Which of the following is most likely a parameter than a statistic a. The proportion of female resisted to vote in a state b. The average height of people randomly selected from a database c. The average score of the first five students completing an assignment d. The proportion of trucks stopped yesterday that were found to be unroadworthy 7) A professor of economics at a Tasmanian university wanted to determine which students were taking his tough economics course. Below is a table showing the results. What percentage of the class are in their honours year a. 86% b. 14% c. 44% d. 54%
8) Retailers are always interested in determining why a customer selected their store to make a purchase. A sporting goods retailer conducted a customer survey to determine why its customers shopped at the store. The results are shown in the bar chart below. What proportion of the customers responded that they shopped at the store because of the merchandise or the prices? a. 20% b. 50% c. 70% d. 85%
A population consist of all the members of a group about which you want to draw a conclusion A sample is the portion of the population selected for analysis A parameter is a numerical measure that describes a characteristic of a population A statistic is a numerical measure that describes a characteristics of a sample
Population and Sample data
Greek letters are used for population data (μ, σ, Ν) Roman letters are used for sample data (x, s, n) A sample is a selection of measurements (subset) from all measurements (population)
Descriptive statistics o Collect data *survey* Important sources *survey, study, data distributed by organisation or a individual* Data sources classified as Primary sources Secondary sources o Present data *tables and graphs*
X
i
n * o Characterise data * sample mean Inferential statistics o Drawing conclusions about a population of data based on the sample data o Estimation *estimate the population mean weight (parameter) using the sample mean weight (statistic)* o Hypothesis testing *testing the claim of a population*
Types of data
Categorical data vs. numerical data o Numerical data (quantitative) is measure on a natural numerical scale Age/share price/number of people in the lecture room/results of 123 Continuous or discrete Continuous – data that can be any real number. Example time to travel to work 54.234 minutes Discrete – countable number or responses, example numbers of students in a lecture room. Can you have half a student? o Categorical data (qualitative) can only be named or categorised Gender/satisfaction very good, good, average, poor Nominal or ordinal Nominal – no natural or implied order No response is considered better Ordinal – there is an implied order Definite order
DATA
(Qualitative)
Numeric al (Quantitative)
Time series or cross sectional o Time series – data collected through time o Cross sectional – data collected for a point in time
Week 1 Quiz 1) The collection and summarisation of the socioeconomic and physical characteristics of the employees of a particular firm is an example of a. Descriptive statistics b. Inferential statistics c. A parameter d. A statistic 2) The estimation of the population average family expenditure of food based on the sample average expenditure of 1,000 families in an example of a. A parameter b. Descriptive statistic c. Inferential statistics d. A statistic 3) The portion of the universe that has been selected for analysis is called a. A statistic b. A parameter c. A frame d. A sample 4) A summary measure that is computed to describe a characteristic of an entire population is called a. A statistic b. The scientific method c. A parameter d. A census 5) Which of the following is most likely a population as opposed to a sample a. Registered users in a stat b. The first 5 students completing an assignment c. Every third person to arrive at the bank d. Responds to a newspaper survey 6) Which of the following is most likely a parameter than a statistic a. The proportion of female resisted to vote in a state b. The average height of people randomly selected from a database c. The average score of the first five students completing an assignment d. The proportion of trucks stopped yesterday that were found to be unroadworthy 7) A professor of economics at a Tasmanian university wanted to determine which students were taking his tough economics course. Below is a table showing the results. What percentage of the class are in their honours year a. 86% b. 14% c. 44% d. 54%
8) Retailers are always interested in determining why a customer selected their store to make a purchase. A sporting goods retailer conducted a customer survey to determine why its customers shopped at the store. The results are shown in the bar chart below. What proportion of the customers responded that they shopped at the store because of the merchandise or the prices? a. 20% b. 50% c. 70% d. 85%
