What does the humanistic perspective emphasized?

What does the humanistic perspective emphasized?

Humanistic psychology is a perspective that emphasizes looking at the whole individual and stresses concepts such as free will, self-efficacy, and self-actualization. Rather than concentrating on dysfunction, humanistic psychology strives to help people fulfill their potential and maximize their well-being.

Which personality theories emphasize reciprocal determinism?

Albert Bandura said that one’s environment can determine behavior, but at the same time, people can influence the environment with both their thoughts and behaviors, which is known as reciprocal determinism. Bandura also emphasized how we learn from watching others.

How does the humanistic perspective define the ideal self?

Rogers further divided the self into two categories: the ideal self and the real self. The ideal self is the person that you would like to be; the real self is the person you actually are. Rogers focused on the idea that we need to achieve consistency between these two selves.

Which perspective on personality emphasizes the importance of our capacity for healthy growth and self realization?


What are the 4 personality theories?

Robert McCrae and Paul Costa: Introduced the big five theory, which identifies five key dimensions of personality: 1) extraversion, 2) neuroticism, 3) openness to experience, 4) conscientiousness, and 5) agreeableness.

Which perspective most clearly emphasizes?

agreeableness. Which perspective most clearly emphasizes that the development of personality is partially learned through conditioning and imitating the behavior of others? reciprocal determinism.

Which perspective is most concerned with how individuals?

Cognitive psychology deals with a person’s thought processes. Perception is often distorted through various cognitive filters. By trying to understand their cognitive processes (journalising through thought dairy, socratic questioning) working through distortions that influence their perceptions of the world.

Which perspective most clearly emphasizes the impact of learning on behavior?

social cognitive perspective

Which measure of variation is most affected by extreme scores?

1 Answer. The Median. An extreme score will skew the value to one side or the other.

Why is the mean sensitive to extreme scores?

The mean is sensitive to extreme scores when population samples are small. For example, for a class of 20 students, if there were two students who scored well above the others, the mean will be skewed higher than the rest of the scores might indicate. Means are better used with larger sample sizes.

Which measure of central tendency is the most sensitive to extreme scores?


Which measure of variation is the most stable?

For normal distributions, all measures can be used. The standard deviation and variance are preferred because they take your whole data set into account, but this also means that they are easily influenced by outliers. For skewed distributions or data sets with outliers, the interquartile range is the best measure.

How do you determine which data set has more variability?

Data sets with similar values are said to have little variability, while data sets that have values that are spread out have high variability. Data set B is wider and more spread out than data set A. This indicates that data set B has more variability.

Is mode a measure of variation?

Three measures of central tendency are the mode, the median and the mean. The variance and standard deviation are two closely related measures of variability for interval/ratio-level variables that increase or decrease depending on how closely the observations are clustered around the mean.

Why is standard deviation considered to be the most reliable measure of variability?

The standard deviation is the standard or typical difference between each data point and the mean. Conveniently, the standard deviation uses the original units of the data, which makes interpretation easier. Consequently, the standard deviation is the most widely used measure of variability.

Why is interquartile range important?

Besides being a less sensitive measure of the spread of a data set, the interquartile range has another important use. Due to its resistance to outliers, the interquartile range is useful in identifying when a value is an outlier. The interquartile range rule is what informs us whether we have a mild or strong outlier.

Why is the range not a good indicator for explaining variability of a data set?

The easiest measure of variability is the range, which is the difference between the highest and lowest scores. For example, Morgan’s range is 6 -•0 = 6. The range is a poor measure of variability because it is very insensitive. By insensitive, we mean the range is unaffected by changes to any of the middle scores.

Which of the following is the least accurate measure of variability?

When comparing between the variability of two characteristics that are measured in different units, social researchers should use the coefficient of variation. Which of the following is the least accurate measure of variability? Scores that have a small standard deviation are relatively inconsistent.

Which measure of central tendency is considered the most precise?


What is the most common measure of variability quizlet?

The standard deviation is the most commonly used and the most important measure of variability.

What does the interquartile range tell you?

The “interquartile range”, abbreviated “IQR”, is just the width of the box in the box-and-whisker plot. The IQR tells how spread out the “middle” values are; it can also be used to tell when some of the other values are “too far” from the central value.

What is the five number summary of a distribution?

A summary consists of five values: the most extreme values in the data set (the maximum and minimum values), the lower and upper quartiles, and the median. These values are presented together and ordered from lowest to highest: minimum value, lower quartile (Q1), median value (Q2), upper quartile (Q3), maximum value.

Which is a better measure of spread range or interquartile range Why?

The interquartile range (IQR) is the difference between the upper (Q3) and lower (Q1) quartiles, and describes the middle 50% of values when ordered from lowest to highest. The IQR is often seen as a better measure of spread than the range as it is not affected by outliers.

How do you find the interquartile range of a data set?

The IQR describes the middle 50% of values when ordered from lowest to highest. To find the interquartile range (IQR), ​first find the median (middle value) of the lower and upper half of the data. These values are quartile 1 (Q1) and quartile 3 (Q3). The IQR is the difference between Q3 and Q1.

How do you find Q1 and Q3 from mean and standard deviation?

Quartiles: The first and third quartiles can be found using the mean µ and the standard deviation σ. Q1 = µ − (. 675)σ and Q3 = µ + (. 675)σ.

How do you find Q1 Q2 and Q3?

In this case all the quartiles are between numbers:

  1. Quartile 1 (Q1) = (4+4)/2 = 4.
  2. Quartile 2 (Q2) = (10+11)/2 = 10.5.
  3. Quartile 3 (Q3) = (14+16)/2 = 15.

What is the 1.5 IQR rule?

Add 1.5 x (IQR) to the third quartile. Any number greater than this is a suspected outlier. Subtract 1.5 x (IQR) from the first quartile. Any number less than this is a suspected outlier.

What is the IQR rule for outliers?

A commonly used rule says that a data point is an outlier if it is more than 1.5 ⋅ IQR 1.5\cdot \text{IQR} 1. 5⋅IQR1, point, 5, dot, start text, I, Q, R, end text above the third quartile or below the first quartile. Said differently, low outliers are below Q 1 − 1.5 ⋅ IQR \text{Q}_1-1.5\cdot\text{IQR} Q1−1.

How do you determine if there are any outliers?

Multiplying the interquartile range (IQR) by 1.5 will give us a way to determine whether a certain value is an outlier. If we subtract 1.5 x IQR from the first quartile, any data values that are less than this number are considered outliers.

What does an IQR of 0 mean?

The IQR is a measure of variability and the mean is a measure of central tendency. Having an IQR of 0 means there is no variability in the middle 50% of your data, but the center of the distribution can be anywhere.