Numerical Data Introduction

• List some Experimental terminology?

  • IV/ independent variable predictor
  • DV/dependent variable outcome
  • Confounds external factors that affect results
  • Error measurment
• Between Groups Design (Random Assignment): This design involves having different participants, participate in different conditions of an experiment
• Within-Subject (Random Assignment): In this design, the same participants receive all levels of the treatment, but in a random order
• Non-Experimental Quantitative Research (Observational): This type of research involves observing and measuring variables without manipulating them.
• Scales of measurement include qualitative categorical (binary, nominal, ordinal), quantitative (interval, ratio)
• Descriptive statistics include?

  • measures of central tendency (mean, median, mode),
  • measures of variability (range, inter-quartile range, standard deviation)
• Sampling from a population includes a normal distribution, law of large numbers, central limit theorem, skewness, kurtosis
• What are the two major types of data used by these scales?

  Qualitiative (catagorical) and Quantitative (numerical)

  A) Qualitative

  B) Quantitative

  
• A number of therapy sessions applies what scale of measurement?

  Discrete scale for quantitative data
• A persons dopamine fluctuation applies to what scale of measurment?

  Continuous scale for quantitative data
• Severity of depression on a scale of 1 to 5 applies to what scale of measurement?

  Ordinal scale used for qualitative variables that have clear, ordered categories and the ranks matter but the differences don't
• Types of mental disorders applies to what scale of measurement?

  Nominal scale used for labeling qualitative variables without any quantitative value
• Intelligence test like the IQ tests are numerically ordered and the difference between scores is meaningful. For instance, the difference in intelligence between an IQ score of 100 and 110 is the same as between 110 and 120. This is an example of what scale measurement?

  Interval scale for quantitative data
• Time taken to respond to a stimulus within experiment applies to what kind of measurement scale?

  Ratio scale for quantitative data as it allows researchers to compare both differences in scores and the relative magnitude of scores
• Examining the impact of therapy type on anxiety reduction, one group might receive (CBT) and the other group (DBT). What type of study design is this?

  Between-groups Design
• Participants try both a mindfulness-based stress reduction technique and a deep breathing exercise in random order to see which is more effective at reducing stress levels. What study design does this best suit?

  Within subjects design
• A Psychologist surveys a group of people at one point in time to find correlations between variables, like the relationship between sleep quality and mental health. What study design does this correlate to?

  Observational correlative design
• Random sampling within study designs is essential to ensure that the sample is representative of the wider population.
• Random sampling helps ensure the validity of the results and allows us to make accurate inferences about the population based on our sample.
• If cause and effect are to be claimed, the sample should always acquire randomisation.
• A researcher measures the same participants at two points in time; test-retest reliability
• Two researchers observe the same behavior independently and compare notes afterwards; Inter-Related Reliability
• This method checks the consistency of results across different versions of the same test; Parallel Reliability
• A researcher checks if the questions on a depression scale all measure the same construct: depression; Internal Consistency Reliability
• Nominal relates to number of verbally ascribed categories
• Ordinal relates to the order of verbally ascribed categories
• interval scale is all about the measure in-between
• Variability helps us to understand how much the data differs from the average or expected value.
• Variation in the context of predictor outcome experiments refers to the degree of spread or difference in the data collected.
• Binary= 2 categories (male/female)

  Nominal= Named categories (Depression, anxiety, OCD)

  Ordinal= Ordered categories (severity of their pain on a scale of 1 to 5)
• Continuous quantitative Variables (1.5, 2.4, 4.8) Integers vs Discrete quantitative Variables (1,2,3) whole numbers.
• Spread of the data from the average is the variability of data
• Clumped mass of the data (mode, median, mean) is the central tendency
• Mode=most common

  Median= Meddle

  Mean= Average
• Continuous is endless, it can be less or more whereas Discrete is complete, it's whole numbers and nothing more.
• continuous variables are like a smooth, unbroken line, versus discrete data being a a dotted line
• Discrete data can only take certain, Distinct values
• A number of students in a class, as you cannot have a fraction of a student. What type of data does this represent?

  Discrete data
• Height as can be measured in centimetres, millimetres, or even smaller units. What kind of data is this?

  Continuous
• Is nominal data continuous or discrete?

  Discrete categories