Key Terms Flashcards
What is a sample?
Individuals selected from a population, intended to represent the population.
What is a variable?
Characteristic or condition that changes or has different values for different individuals.
And is the operalization of a construct/concept.
What is data? A data set?
A score (singular), single measurement. Data set is a collection of measurements.
What are the two types of statistical methods?
Descriptive and inferential.
Descriptive are the basic info, tables and characteristics of the sample. They are used to summarise, organise and simplify the data.
Inferential is where you answer your research question. It is the techniques that allows us to study samples and then make generalisations about the populations.
How can you minimise sampling errors?
- A larger sample size or 2. through different sampling methods.
What are 2 sampling methods?
- Probability sampling: simple random sample, systematic sample, stratified sample, cluster sample (random subgroups first).
- Non Probability sampling: subjective, based on judgement of research. For example, convenience sampling or snowball sampling. It is hard to be representative.
What are the key aspects of a good research question?
It should be original: something new should be included. It should be specific, researchable/feasible and meaningful to save practical problems.
How are hypothesis formed?
H0 - The null hypothesis, this is what is considered first.
H1 - alternative hypothesis. Competes with null hypothesis.
What are variables?
Variables are the operalization of a concept/construct.
What are some examples of nominal scales/categories?
Something with no ranking between categories. Names/Categorical/Different Names. Ex: Nationality, gender, major of study.
What are some examples of ordinary scales/categories?
Something with ranking between categories. These are sets that can be ordered in a sequence, though the interval may not be equal. Ex: Ranking in sports, dress size, level of education.
What are some examples of interval scales/categories?
There is no true “0” score, the value can go below 0. Ex: Temperature.
What are some examples of ratio scales/categories?
Ordered categories of exactly same size, whole #s or fractions. 0 true value. Never falls below 0. ex: age, weight.
What are the two criteria to judge if your measurement is good?
Reliability: can you produce consistent results over time?
Validity: Does is measure what it is supposed to measure?
What are the 3 types of research methods?
- Correlational method (observe two variables as they exist naturally. Is there a relationship between them?).
- Experimental study (can analyse cause and effect. Difficult as you have to manipulate a condition, one variable).
- Longitudinal study (repeated cross sectional studies, prospective studies, retrospective studies. Anything that is studied more than once).
What is the correlational method of research?
Observing two variables as they exist naturally. Is there a relationship between them? Limits: you can’t determine cause and effect.
What is an experimental study?
A study in which you manipulate a variable or condition. You can analyse cause and effect. Independent variable is the cause, which is manipulated. (The type of medicine, yoga vs cardio). The dependent variable is the effect, the outcome. This is what is observed and measured to assess the effect of the treatment.
What is a quasi experimental method?
An experiment in which you are just observing and not interfering. You observe the independent variable without manipulating it, and measure the dependent variable.
What is the independent variable vs the dependent variable?
The independent variable is manipulated, it is the cause. For example, the type of medicine, or yoga vs cardio.
The dependent variable is the effect, the outcome. This is what is observed and measured to assess the effect of the treatment.
What are the three types of longitudinal studies?
Repeated cross sectional studies (trend studies), prospective studies (same participants followed over time) and retrospective studies (designed after some have experienced events of relevance.
Speak to the shape of frequency distribution.
1 - the shape: is it symmetrical? Bell shape is normal. The mean, median and mode over lap in the highest part of the bell. Positive skew (the tail of the chart points toward the positive, above 0, left to right). Negative skew.
2 - the central tendency: the mean, median and mode.
What is the mean?
It is the average. There is a population mean vs a sample mean. The weighted mean is calculated by combining the two samples to calculate the overall mean.
What is the median?
It divides the set into two equal parts, and finds the middle number. Without outliers or extreme values, this is a good measure.
What is the mode?
Mode is the greatest frequency. It could be multiple and is not affected by extreme values. It describes qualitative data.
What is variability?
Variability, also dispersion, shows us the differences between scores in a distribution and describes the degree to which the scores are spread out or clustered. If there are small differences between scores, then variability is small. If there are large differences between scores, then variability is large.
When do we have normal distribution? (Also called Gaussian distribution)
Commonly occurring shape for probability distributions. Includes 4 things:
1. It is symmetrical around its mean.
2. The mean, the median and the mode are all equal.
3. The symmetry, already mentioned, 50% of the area is to the right and 50% of the left.
4. Normal distribution is completely determined by the parameters u and o.
If kurtosis and skewness are both in the range of -1 to +1, there is normal distribution.
What is the mean and standard deviation?
The mean is 80 (represented by the line in the middle of this frequency distribution graph) and the standard deviation is 8 (represented by the sigma sign in the graph).
Identify the range and quartiles.
Definition of probability?
The probability of a specific outcome is defined as a fraction or proportion of all the possible outcomes.
In SPSS, what is a quick way to look at important descriptive statistics from your data?
Select the row of variable you are interested in, right click and select “descriptive statistics”.
What are 3 characteristics of the distribution of sample means?
1 - The sample means should pile up around the population mean.
2 - The pile of sample means should tend to form a normal-shaped distribution.
3 - In general, the larger the sample size, the closer the sample means should be to the population mean.
Logistically, a large sample should be better representative than a small sample.
What is the central limit theorem?
Central Tendency
Standard Error
Shape
Central tendency: the mean of the distribution sample means is equal to the mean of the population scores and is called the expected value of M.
Standard Error: The standard deviation of the distribution of sample means, M, is called the standard error of M. The standard error provides a measure of how much distance is expected on average between a sample mean M and the population mean given a specific sample size.
Shape: Law of large numbers states that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean.
Explain H0 and H1.
How do you set the decision criteria?
By defining the alpha level or level of significance. The critical region is composed of the extreme sample values that are very unlikely, to be obtained if the null hypothesis is true.
What are the types of errors?
Type I Error: Researcher rejects a null hypothesis that is actually true. In a typical research situation, a Type 1 error means that the researcher concludes that a treatment does have an effect when, in fact, it has no effect. Alpha level is the probability that the test will lead to a type I error.
Type II Error: Occurs when a researcher fails to reject a null hypothesis that is really false. In a typical research situation, a Type 2 error means that the hypothesis test has failed to detect a real treatment effect. Probability of type II error is represented by the symbol B, beta.
What is the effect size?
A measure of effect size is intended to provide a measurement of the absolute magnitude of a treatment effect, independent of the size of the sample(s) being used.
Cohen’s d evaluates the effect size.
When do you use sample variability?
When the variability for a population is not known, we use sample variability. The result of the new test statistic, called “t statistic”.
