Term | Definition |
Statistics | The science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data. |
Variable | A characteristic or attribute that can assume different values. |
Data | The values the variables assume. |
Random Variables | Variables whose values are determined by chance. |
Data Set | A collection of data values. |
Data Value (Datum) | Each value of the data set. |
Probability | The chance of an event occuring. |
Population | All subjects that are being studied. |
Sample | A group of subjects that are being studied. |
Hypothesis Testing | A decision-making process for evaluating claims about a population based on information from samples. |
3 ways statistics is used in everyday life | 1. used in fields of human endeavor-sports, public health, and education.
2. used to analyze the results of a survey.
3. Used as a tool in scientific research to make decisions based on controlled experiments. |
3 reasons to study statistics | 1. To be able to understand statistical studies.
2. To be able to conduct research, design experiments, make predictions and communicate results.
3. To become better consumers. |
Descriptive statistics | consists of the collection, organization, summarization, and presentation of data |
Inferential statistics | consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions. |
Quantitative variables | numerical and can be ordered or ranked.
ex. Age, height, weight |
Qualitative variables | variables that can be placed into distinct categories (like a characteristic or attribute)
ex. gender, color, religious preferences |
Discrete variables | variables that assume values that can be counted
ex. # of children, # of students |
continuous variables | variables that can assume an infinite number of values between any two specific values. They are obtained by measuring- often contain fractions. |
Nominal level of measurement | classifies data into mutually exclusive (non-overlapping) exhausting categories in which no order or ranking can be imposed on the data
ex. gender, zip code, political party |
Ordinal level of measurement | classifies data into categories that can be ranked, however, precise differences between the ranks do not exist.
ex. ranking guest speakers, classifying a person's build |
Interval level of measurement | ranks data and precise differences between units of measure do exist, however, there is no true zero.
ex. IQ test, temp., SAT scores |
Ratio level of measurement | possesses all the characteristics of interval measurement and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different numbers of the population.
ex. height, weight, area, # phone calls, time, salary |
2 purposes of data collection | 1. To describe situations or events
2. To help people make better decisions before acting |
3 ways to collect data | 1. surveys
2. surveying records
3. direct observations |