Types of data.

Qualitative & quantitative

Quantative Data is expressed in numbers

  • One advantage of this data type is that it is easier to analyse and determine.
  • One disadvantage of this data type is that it may oversimplify or under estimate the topic due to vague questions

Qualitative data is expressed in words

  • This data can be very representative and account for more detail in the study.
  • This data however, is more difficult to collect and less easier to analyse.
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Primary, secondary and meta-analysis

Primary data is data that is collected first hand that fit the purpose of the study.

  • The data collected is relevant and will effect the ending result, this could increase reliabillity.
  • Requires time and effort

Secondary data is data that is obtained by someone else outside the experiment.

  • Inexpensive and quick to gather data.
  • Quality of data maybe poor as it could be outdated.

Meta-analysis is secondary data on a large scale, multiple studies

  • Increases validity as data collected is on a large scale meaning the results will be more clear.
  • Researcher may avoid data that doesn't coincide with the results.
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Measures of central tendency.

Mode is the most common value in category data and numeral data.

  • One benefit is that it is relevant to categories, when data is represented in categories sometimes mode is the most appropriate.
  • One drawback is that it fails to desribe that data as there could be more than one mode in data.

Median value is the middle value in the data, if two medians are selected then they are added together divided by how many there are e.g. 2.

  • Unaffected by extreme scores, because it is only concerned with the middle value.
  • However, some extreme values need to be used just incase.

Mean is the outcome of all the values added together and divided by how many there are.

  • Inlcludes all data so it is representative.
  • Sensitive as one large or small number can make a big difference.
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Measures of distribution.

Range is the difference between highest and lowest value.

  • Easy to calculate, put in order then takeaway the lowest from highest, this means it is quick.
  • Range does not indicate whether values are closely grouped together or evenly distributed as only two values are used.

Standard deviation is a measure of the average spread around the mean, the larger the deviation, the more spread out the data is.

  • More precise than the range as it includes all values.
  • Misleading as it may hide extreme values which could cause concern for the validity of the results.
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