Chapter 1- Introduction and Basic Concepts Flashcards

1
Q

Data

A

a set of scores, measurements, or observations that are typically numeric. A datum (singular) is a single measurement or observation, usually referred to as a score or raw score.

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2
Q

Descriptive statistics

A

procedures used to summarize, organize, and make sense of a set of scores called data. Descriptive statistics are typically presented graphically, in tabular form (in tables), or as summary statistics (single values)

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3
Q

General Structure for Making Scientific Observations

A
  1. Ask a question
  2. Set up a research study
  3. Evaluate findings
  4. Measure behavior
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4
Q

Inferential statistics

A

procedures used that allow researchers to infer or generalize observations made with samples to the larger population from which they were selected

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5
Q

population

A

the set of all individuals, items, or data of interest. This is the group about which scientists will generalize.

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6
Q

population parameter

A

A characteristic (usually numeric) that describes a population

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7
Q

sample

A

a set of individuals, items, or data selected from a population of interest.

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8
Q

sample statistic.

A

A characteristic (usually numeric) that describes a sample

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9
Q

Science

A

the study of phenomena, such as behavior, through strict observation, evaluation, interpretation, and theoretical explanation.

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10
Q

The research method, or scientific method

A

a set of systematic techniques used to acquire, modify, and integrate knowledge concerning observable and measurable phenomena.

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11
Q

experiment

A

the use of methods and procedures to make observations in which a researcher fully controls the conditions and experiences of participants by applying three required elements of control (manipulation, randomization, and comparison/control) to isolate cause-and-effect relationships between variables.

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12
Q

Random assignment

A

a random procedure used to ensure that participants in a study have an equal chance of being assigned to a particular group or condition.

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13
Q

independent variable (IV

A

the variable that is manipulated in an experiment. This variable remains unchanged (or “independent”) between conditions being observed in an experiment. It is the “presumed cause.” The specific conditions of an IV are referred to as the levels of the independent variable.

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14
Q

dependent variable (DV)

A

the variable that is measured in each group of a study, and is believed to change in the presence of the independent variable. It is the “presumed effect.”

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15
Q

operational definition

A

a description of some observable event in terms of the specific process or manner by which it was observed or measured.

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16
Q

quasi-independent variable

A

a preexisting variable that is often a characteristic inherent to an individual, which differentiates the groups or conditions being compared in a research study. Because the levels of the variable are preexisting, it is not possible to randomly assign participants to groups.

17
Q

quasi-experiment

A

The study does not include a manipulated independent variable.
The study lacks a comparison/control group.

18
Q

Scales of measurement

A

identify how the properties of numbers can change with different uses. Four scales of measurement are nominal, ordinal, interval, and ratio.

19
Q

Nominal scales

A

measurements in which a number is assigned to represent something or someone.

20
Q

Coding

A

the procedure of converting a nominal or categorical variable to a numeric value.

21
Q

Ordinal scales

A

measurements that convey order or rank alone

Examples of ordinal scales include finishing order in a competition, education level, and rankings

22
Q

Interval scales

A

measurements that have no true zero and are distributed in equal units.

A common example for this in behavioral science is the rating scale

23
Q

equidistant scale

A

a set of numbers distributed in equal units.

24
Q

Ratio scales

A

A ratio scale is equidistant, has a true zero, and is the most informative scale of measurement.

25
Q

continuous variable

A

measured along a continuum at any place beyond the decimal point. A continuous variable can thus be measured in fractional units.

26
Q

discrete variable

A

measured in whole units or categories that are not distributed along a continuum.

27
Q

quantitative variable

A

varies by amount. This variable is measured numerically and is often collected by measuring or counting.

28
Q

qualitative variable

A

varies by class. This variable is often represented as a label and describes nonnumeric aspects of phenomena.

29
Q

What is the difference between data and a raw score?

A

Data describe a set of measurements (made up of raw scores); a raw score describes individual
measurements.

30
Q

A researcher measured behavior among all individuals in a small population. Are inferential statistics necessary to draw conclusions concerning this population? Explain.

A

in situations where the researcher has complete information about the population, inferential statistics are not necessary. The researcher can use descriptive statistics to summarize the behavior of the individuals in the population and draw conclusions based on that information.

31
Q

What are the two types of variables that are quantitative?

A

Continuous and discrete