Data Analysis - Types of Data Flashcards

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1
Q

What is qualitative data?

A

Data that is displayed in words and is non-numerical.

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2
Q

What is a strength of qualitative data?

A

It offers more richness and depth of detail, allowing participants to fully express their views.

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3
Q

What is a limitation of qualitative data?

A

It is difficult to analyze and make comparisons with other data, and there may be researcher bias due to subjective interpretations.

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4
Q

What is quantitative data?

A

Data that is displayed numerically, not in words.

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5
Q

What is a strength of quantitative data?

A

It can be analyzed statistically and displayed in graphs or charts, making it easy to compare with other data.

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6
Q

What is a limitation of quantitative data?

A

It lacks depth of detail and does not provide meaningful insight into participants’ opinions.

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7
Q

What is primary data?

A

Data obtained firsthand by the researcher for a specific investigation.

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8
Q

What is a strength of primary data?

A

It targets the exact information the researcher needs, so the data fits their aims and objectives perfectly.

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9
Q

What is a limitation of primary data?

A

It requires time, effort, and can be expensive to collect.

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10
Q

What is secondary data?

A

Data collected by someone other than the researcher and then used by the researcher in their study.

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11
Q

What is a strength of secondary data?

A

It is inexpensive and quick to access, requiring minimal effort to collect.

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12
Q

What is a limitation of secondary data?

A

It may be outdated, incomplete, or unreliable as the researcher was not present when it was collected.

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13
Q

What is meta-analysis?

A

A method where a researcher combines results from many different studies to get an overall view of the subject being investigated.

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14
Q

What is a strength of meta-analysis?

A

It increases generalizability as it includes a larger amount of data, giving the researcher more confidence in the results.

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15
Q

What is a limitation of meta-analysis?

A

Publication bias can occur (file drawer problem), where only positive results are published, leading to a false representation of the research.

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