1
1003PSY Stats 1
Module 1: recap
• Theory, hypothesis, test, evidence and theory
• Negative skew- tail left, positive skew- tail right
• Positive kurtosis- heavier tails, more outliers, negative kurtosis- no tail,
almost at
• Unimodal- one peak, one mode. Bimodal- more peaks and more than
one mode
Module 2:
• Median- middle
• Mode- most repeated value
• Mean- average
• Positively skewed- mean right, negatively skewed- mean left
• Which measure to use:
• Categorical data- mode
• Continuous data- if it is skewed- median, if not skewed, normal distribution-
mean
• Spread/ variability- quartiles (median, nd lowest score in middle….answer
in slide for lec 2), standard deviation (square root of deviation), range(min.
And max, biggest to smallest no.), variance (how much the scores di er
from the mean)
• Range is least a ected by outliers (extreme scores)
Module 3:
• Mode biggest part in the pie chart
• Histogram- single distribution on x axis, bar graph- group of scores on x
axis
• Box in box plot, interquartile range, lines, lower and upper cuto
• Outliers, count no. of dots, positive skew, median clumped left, whisker
longer. Negatively skewed- longer whisker towards negative scores,
median towards the right
• Flow chart of which measure to use in slides in lecture 2
• Skewed Dist. Box plot
• Many outliers- box plot
• Normal distr. mean and stand. Dev. Histogram
• Scatter plots, positive relationship- increase in one value leads to an
increase in another value (line goes towards right), negative relationship,
increase in one value does not lead to an increase in the other value( line
goes towards left)
• Outliers- dots that deviate a lot from the group of dots
• Step 1= mean, step 2: variance (how to calculate in leg slides), step 3:
standard deviation. dev (root of variance)
Module 4:
• Normal dist. Any can be converted to a standard normal distribution
fl ff fi ff ff
, 2
• Z score, how many stand. Deviation Scores are the mean away from the
max. Ex. Curve of 80,90,100,110,120. With 100 mean, z score is 2 places
away from the mean so z score = 2
• You can use this to nd probabilities and proportions
• 68-95-99.7 rules for the z-table
%= proportion *100 in the z table
Reporting results:
results:
• Vari. Of interest- interested in testing with hyp.
• Comment on the shape of data, skew, kurtosis, modality, and outliers
• Two nos. and one pic for data, one measure of central tendency, one
measure of spread, do the same two descriptions for both variables
• Make scatter plots
• Explan vary. On x axis, and the response variable. Y-axis, and scatter plots
for all 3 variables. And MAKE THEM APA FORMAT
• Conduct a correlation spearman or Pearson correlation, and report the
correlation. Coef, and p value, signif. Or not and positive or -ve rela. Explain
about when one variable. the other increase or vice versa
• Interpret. Was it consistent with the hyp and why
• What do your ndings give new info about the eld
• Study limitations, what could be done better to improve future research
• Summarise what you say and say the key message of resreach, what’s one
thing you want others to remember about your research, take-home
message
fi fi fi
1003PSY Stats 1
Module 1: recap
• Theory, hypothesis, test, evidence and theory
• Negative skew- tail left, positive skew- tail right
• Positive kurtosis- heavier tails, more outliers, negative kurtosis- no tail,
almost at
• Unimodal- one peak, one mode. Bimodal- more peaks and more than
one mode
Module 2:
• Median- middle
• Mode- most repeated value
• Mean- average
• Positively skewed- mean right, negatively skewed- mean left
• Which measure to use:
• Categorical data- mode
• Continuous data- if it is skewed- median, if not skewed, normal distribution-
mean
• Spread/ variability- quartiles (median, nd lowest score in middle….answer
in slide for lec 2), standard deviation (square root of deviation), range(min.
And max, biggest to smallest no.), variance (how much the scores di er
from the mean)
• Range is least a ected by outliers (extreme scores)
Module 3:
• Mode biggest part in the pie chart
• Histogram- single distribution on x axis, bar graph- group of scores on x
axis
• Box in box plot, interquartile range, lines, lower and upper cuto
• Outliers, count no. of dots, positive skew, median clumped left, whisker
longer. Negatively skewed- longer whisker towards negative scores,
median towards the right
• Flow chart of which measure to use in slides in lecture 2
• Skewed Dist. Box plot
• Many outliers- box plot
• Normal distr. mean and stand. Dev. Histogram
• Scatter plots, positive relationship- increase in one value leads to an
increase in another value (line goes towards right), negative relationship,
increase in one value does not lead to an increase in the other value( line
goes towards left)
• Outliers- dots that deviate a lot from the group of dots
• Step 1= mean, step 2: variance (how to calculate in leg slides), step 3:
standard deviation. dev (root of variance)
Module 4:
• Normal dist. Any can be converted to a standard normal distribution
fl ff fi ff ff
, 2
• Z score, how many stand. Deviation Scores are the mean away from the
max. Ex. Curve of 80,90,100,110,120. With 100 mean, z score is 2 places
away from the mean so z score = 2
• You can use this to nd probabilities and proportions
• 68-95-99.7 rules for the z-table
%= proportion *100 in the z table
Reporting results:
results:
• Vari. Of interest- interested in testing with hyp.
• Comment on the shape of data, skew, kurtosis, modality, and outliers
• Two nos. and one pic for data, one measure of central tendency, one
measure of spread, do the same two descriptions for both variables
• Make scatter plots
• Explan vary. On x axis, and the response variable. Y-axis, and scatter plots
for all 3 variables. And MAKE THEM APA FORMAT
• Conduct a correlation spearman or Pearson correlation, and report the
correlation. Coef, and p value, signif. Or not and positive or -ve rela. Explain
about when one variable. the other increase or vice versa
• Interpret. Was it consistent with the hyp and why
• What do your ndings give new info about the eld
• Study limitations, what could be done better to improve future research
• Summarise what you say and say the key message of resreach, what’s one
thing you want others to remember about your research, take-home
message
fi fi fi
