# RM IV

Statistics - science - collecting, organizing, interpreting

Norm - Average 50% population

Mean - a type of average where the sum total is divided by the number of elements

# Measurement

the process of assigning numbers or labels to units of analysis in order to quantify or categorize them. Measurement allows researchers to describe and compare their data using a common metric.

# Measurement Scales

• Nominal measurement is the simplest form of measurement. It involves assigning labels or names to units of analysis without implying any order or magnitude. For example, assigning a number for a gender,
• Ordinal measurement involves assigning ranks or orders to units of analysis based on some criterion. It implies that there is a meaningful sequence among the categories, but not that the intervals between them are equal.
• Interval measurement involves assigning numbers to units of analysis such that the intervals between them are equal and meaningful. It implies that there is a zero point, but not that it represents an absolute absence of the variable. For example, temperature
• Ratio measurement involves assigning numbers to units of analysis such that the intervals between them are equal and meaningful, and there is a true zero point that represents an absolute absence of the variable. For example, sales, income, costs, age, and height are ratio variables.

# Errors in measurement

• respondent
• situation
• instrument
• researcher/measurer

# Testing Measurement

Reliability (of a tool) refers to consistency of the tool. The tool must give the same / similar results no matter how many tries / testing and retesting.

Validity is the extent to which the tool measures what it is intended to measure

standardization - making norms

validity is about the accuracy of a measure, i.e., how well it measures what it is supposed to measure. Reliability is about the consistency of a measure, i.e., how well it produces the same results under the same conditions. A measurement can be reliable without being valid, but a valid measurement is usually also reliable. For example, if you use a broken thermometer to measure the temperature of a liquid sample several times, you might get the same reading every time (reliable), but it does not reflect the true temperature of the sample (invalid). On the other hand, if you use a working thermometer to measure the temperature of a liquid sample several times, you should get the same reading every time (reliable) and it should match the true temperature of the sample (valid).

read also - accuracy vs precision

and Practicality

Finding Norms - Plot graph Calculate Mean -1 sigma +1 sigma -> 68% -2 to +2 -> ~ 90%

Q) Importance of statistical in psychological research. defn of stats defn of psychological research

Normal Probability Curve how we generalize

Zeigarnik Effect

Measurement - Assigning a numerical value to the variable of the study

see also: Beck's Depression Scale Youth Self Assesment Scale - x = 50 sigma - 10 pathologization of normal behaviour neurodivergency