QM 1, Flashcards

1
Q

The study of how best to collect, analyze, and draw conclusions from data.​

A

Statistics​

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2
Q

the backbone of a statistical investigation.​

A

​​​​Data

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3
Q

the creation of new knowledge and/or the use of existing knowledge in a new and creative way so as to generate new concepts, methodologies and understandings.​

A

Research

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4
Q

any information that has been collected, observed, generated or created to validate original research findings.​

A

Research Data​

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5
Q

Concepts, characteristics, or properties that can vary, or change, from one unit of analysis to another. ​

A

Variables

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6
Q

Variables that the researcher wishes to explain.​

Is an effect or result, and it always depends on another factor. The goal of an experiment or study is to explain or predict the dependent variables caused by the independent variable​

A

Dependent Variable (DV)

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7
Q

Variables that help explain the change in the dependent variable.​

Stands alone and isn’t affected by other variables​

A

Independent Variable (IV)​

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8
Q

An empirical statement which seeks to test the relationship between at least two variables. ​

A

Hypothesis

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9
Q

Use of the following are very common displays used in reports:​

  1. Tables​
  2. Bar charts​
  3. Pie charts​
  4. Histograms​
  5. Scatter diagrams​
A
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10
Q

Tables work best when the data presentation:​

Is used to look up or compare individual values​

Requires precise values​

Values involve multiple units of measure​

A
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11
Q

Graphs work best when the data presentation:​

Is used to communicate a message that is contained in the shape of the data​

Is used to reveal relationship among many values​

A
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12
Q

Categories of​

Research Data​

A

Categorical​

Numerical​

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13
Q

These data are expressed by means of a natural language description.​

A

Categorical Data​

(Qualitative Data)​

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14
Q

They represent characteristics such as a person’s :​

  • gender,​
  • marital status​
  • hometown, or​
  • types of movies they like.​
A
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15
Q

Values or observations can be assigned a code in the form of a number where the numbers are simply labels. ​

A

Nominal Data​

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16
Q

Values or observations can be ranked (put in order) or have a rating scale attached. ​

A

Ordinal Data​

17
Q

such as a person’s height, weight, Intelligence Quotient (IQ), or blood pressure.​

A

Measurement​

18
Q

such as how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep.​

A

Count​

19
Q

Measurements.​

Their possible values cannot be counted and can only be described using intervals on the real number line.​

can take any value (decimal numbers)​

A

Continuous Data​

20
Q

Items that can be counted.​

Certain values​

A

Discrete Data

21
Q

Grouping method​

Hypothesis testing​

Chi-squared test - aims to determine whether there is a significant difference between the expected frequency and the observed frequency of the given values.​

A

Nominal (labels)​

22
Q

charts such as pie chart.​

A

Visualization Tools

23
Q

accepting or rejecting a claim.​

A

Hypothesis testing

24
Q

used to test whether there is a significant mean difference between two sets of paired data.​

A

Matched-paired test

25
Q
A