Descriptive Statistics

• What is Quantitative Data?

  • Numerical formed data.
• What is Qualitative Data?

  • Non-numerical formed data (descriptive or written words.)
• Strength of Quantitative Data

  • Allows for easy comparisons to be made SO can draw valid conclusions.
• Weakness about Quantitative Data

  • Limited insight to people’s behaviour SO limited usefulness to overall results.
• Strength of Qualitative Data

  • Gains insight into certain behaviours SO is more useful.
• Weakness of Qualitative Data

  • Hard to make comparisons SO reduces usefulness.
• What is Primary Data?

  Researchers collected data first hand through experiments.
• What is Secondary Data?

  Using already gathered information from other people from places like the internet.
• Strength of Primary Data

  • Researchers are in control SO it ensures the data is collected correctly.

  • This allows for more faith in validity of findings.
• Weakness of Primary Data

  • Researchers need to plan a suitable and ethical procedure to collect the data they want WHICH will be time consuming.
• Strength of Secondary Data

  • Data already exist SO it is less time consuming and easy to access.
• Weakness of Secondary Data

  • Quality of data will be subject to any weaknesses present in the original study SO will reduce validity of findings.
• What are the 3 levels of measurements when collecting data?

  Nominal, Ordinal, Interval and Ratio.
• What is Nominal Data?

  • Categorical data.

  • It is nominal if it doesn’t have individual scores.
• What is Ordinal Data?

  • It is categorical data that is ranked or ordered.

  • It is not ordinal if it doesn’t have scientific measurements.
• What is Interval and Ratio Data?

  • Categorical data that is ranked with scientific units.

  • Interval if it CAN go into negative numbers and Ratio if not.
• Strength of Nominal Data

  • Easy to analyse.
• Weakness of Nominal Data

  • Doesn’t allow for comparison between participants DUE TO no individual scores.
• Strength of Ordinal Data

  • Allows for some comparisons as participants scores are sometimes ranked in order.

  • Data can be simplified.
• Weakness of Ordinal Data

  • Doesn’t allow us to see differences between the participants scores.

  • Data isn’t scientific units.
• Strengths of Interval and Ratio Data

  • Measured in scientific units allowing for detailed comparisons between participants scores.

  • Data can be simplified.
• What are the 3 Measures of Central Tendency?

  • Mean

  • Median

  • Mode
• What are the 3 Measures of Dispersion?

  • Range

  • Variance

  • Standard Deviation
• What is the Mean?

  Add up all the scores and divide them by the total number of scores.

  • Most suitable for interval/ratio and ordinal data.
• Strength of the mean

  Uses all the raw data.
• Weakness of the mean

  Misleading as the result can be affected by extreme scores.
• What is the median?

  Data placed in order and you will find the middle value.

  • If 2 middle numbers, add them together and then divide by 2.

  • Most suitable for ordinal data.
• Strength of the median

  Not affected by extreme scores.
• Weakness of the median

  • Can be distorted by small samples (e.g. 2,3,5,98,112, median = 5.)
• What is the mode?

  The score that occurs the most frequently.

  • If there are 2 modes then both are the final score (bi-modal.)

  • Most suitable for nominal data.
• Strength of the mode

  • Shows the most popular value and isn’t affected by extreme scores.
• Weakness of the mode

  • Doesn’t use all the data SO may not be representative.
• What is the range?

  The difference between the highest and lowest scores (+1 for measurement errors.)

  • Most suitable for interval/ratio and ordinal data.
• Strength of the range

  • Easy to calculate.
• Weakness of the range

  •Can be influenced by extreme scores SO may be misleading as it doesn’t tell us the distribution of other scores.
• What is the variance?

  Considers the difference between each data point and the mean.

  • Tells us more about the range.
• Strength of the variance

  • Takes every score into account SO not affected by outliers.
• Weakness of the variance

  • Data is not in line with the original data set.
• What is the standard deviation?

  Tells us the spread of data around the mean.

  • Can see whether data is closely clustered or spread out from the mean.
• Strength of the standard deviation

  • More in line with the original data set.