chapter 1 data and problem solving. section 1.1 getting started
TRANSCRIPT
Chapter 1 DATA AND PROBLEM SOLVING
Section 1.1 GETTING STARTED
Vocabulary
Statistics – The science of gathering, describing and analyzing data or the actual numerical descriptions of sample data.
Population – The particular group of interest.
Data – Information prepared for a study
Census – When data is obtained from every member of the population.
Parameter – A numerical description of a particular population characteristic.
Sample – A subset of the population from which data is collected.
Sample Statistic – The actual numerical description of a particular sample characteristic.
Two Types of Statistics
Descriptive Statistics –
Inferential Statistics -
Example 3
Descriptive
Example 4
Inferential
Section 1.2 LEVEL OF MEASUREMENT
Qualitative vs. Quantitative
Labels or descriptions of traits of the sample Categorical
Examples
Foods
Places
Colors
Identification Numbers
Counts and measurements Numerical
Examples
Test scores
Average rainfall
Median heights
Continuous vs. Discrete
Data that can take any value within an interval Cannot be counted
Examples
Measurements
Time
Temperature
Data that refers to individual data that is countable Can be counted
Examples
Number of pets
Levels of Measurement
Example 1
Qualitative
Neither
Nominal
Example 2
Quantitative
Continuous
Ratio
Section 1.3 THE PROCESS OF A STATISTICAL STUDY
Ways to Collect Data
Sampling Methods
RandomEvery member of the population has an equal chance of being selected.
Example:
Drawing names from a hat.
Stratified The population is divided into groups based on a characteristic, then members from each group are chosen randomly.
Example:
Separating students by class, then randomly choosing 5 from each class.
Cluster The population is divided into groups that are similar to the population, then groups are chosen at random to sample.
Example:
Dividing students so there are 10 of each class in a group, then choosing 2 groups to sample.
Sampling Methods cont.
SystematicThe population is aligned in no specific order then every nth member is chosen.
Example:
Choosing every 5th person.
ConvenienceChoosing a sample the is “convenient” to the researcher.
Example:
Teacher surveying students from one of their classes to represent the population.
Types of Studies
Single-blind vs. Double-blind
Additional Vocabulary
Section 1.4 THE REALITY OF CONDUCTING A STUDY
Institutional Review Board
A group of people who review the design of a study to make sure that it is appropriate and the no unnecessary harm will come to the subjects involved.
Ethical and Practical Concerns
Informed ConsentCompletely disclosing to participants the goals and procedures involved in a study and obtaining their agreement to participate.
Biased A study tends to favor certain results
Researcher BiasWhen the researcher influences the results of the study to favor a certain outcome.
Sampling ErrorsErrors resulting from the way the sample is chosen
DropoutA participant who begins the experiment but then fails to complete it.
Participation BiasWhen there is a problem with either the participation – or lack thereof – of those chosen for the study.
Non-sampling ErrorsOccur from sources other than the construction of the sample.
Processing Errors A type of non-sampling error that occurs in the reporting, could be a typo in the data set.
Non-adheresSubjects who stray from the directions they were given, but remain in the sample to the end.
Confounding VariablesVariables that the researcher did not account for.