7. RESEARCH METHODS (Graphs (Presentation of quantitative data, the maths bit and distributions)) Flashcards
What is the purpose of presenting quantitative data in graphs and tables?
Graphs and tables help to summarize and display data in a clear and concise manner, making it easier to analyse and interpret the findings.
What is the use of a pie chart in presenting quantitative data?
A pie chart is used to display the frequency of categories as percentages, with each section representing a category and its corresponding percentage.
How is a frequency polygon (line graph) used to present continuous data?
A frequency polygon plots continuous data on the x-axis (scores) and the frequency of those scores on the y-axis. Data points are connected by a line to form the graph.
How do bar charts display data?
Bar charts show data in categories along the x-axis with frequencies on the y-axis. The bars are separated by spaces to show that the categories are not continuous.
What is the purpose of using histograms?
Histograms are used for continuous data. The x-axis represents continuous values, and the y-axis shows the frequency of each value. The bars are adjacent to each other, with no spaces between them.
What should you avoid when interpreting or writing conclusions from graphs and tables?
Avoid merely describing the graph or table. Instead, explain the implications of the findings and support your conclusion with specific numbers from the graph or table.
What is a normal distribution?
A normal distribution is a bell-shaped curve that is symmetrical at the midpoint. In this distribution, the mean, median, and mode are all at the centre, and scores are evenly spread around the mean.
What are key characteristics of a normal distribution?
A normal distribution has a bell-shaped curve, with the mean, median, and mode at the centre. 68.26% of the data lies within one standard deviation of the mean, and 95.44% lies within two standard deviations.
How do percentages relate to normal distribution?
In a normal distribution, 68.26% of the population will fall within one standard deviation from the mean, while 95.44% will fall within two standard deviations.
What is a skewed distribution?
skewed distribution occurs when the data is not symmetrically distributed, and the mean, median, and mode do not coincide. The distribution has a tail on one side, either to the left (negative skew) or right (positive skew).
What happens in a negative skew?
In a negative skew, most scores are clustered on the right side, with a few extreme low scores pulling the mean to the left. The mode is higher than the median, and the median is higher than the mean.
What happens in a positive skew?
In a positive skew, most scores are clustered on the left side, with a few extreme high scores pulling the mean to the right. The mode is lower than the median, and the median is lower than the mean.
How can you determine if a distribution is positively or negatively skewed?
You can determine the skew by looking at the tail of the distribution. A positive skew has a tail to the right (higher scores), and a negative skew has a tail to the left (lower scores).
Can you provide an example of a positive skew in real life?
An example of a positive skew is a test of depression where most people have low scores (normal behaviour) and only a few people score very high, indicating clinical depression.
Can you provide an example of a negative skew in real life?
An example of a negative skew is an exam that is very easy, where most students score very high, and only a few score low.
