# Psychological Statistics Exam 2

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Chapters 4 through 6.

location

### With respect to other scores in a distribution, measures of central tendency...

are the points around which most of the scores are located

### In order to decide which measure of central tendency is appropriate, you must first determine

the scale of measurement being used and the shape of the distribution

### The mode is defined as

the most frequently occurring score

nominal

mode

### The median is defined as

the point at or below which 50% of the scores fall

median

### The median is the preferred measure of central tendency when

the scale of measurement is ordinal

### Why si the median unaffected by extreme scores occurring in only one tail of the distribution?

Because the median doesn't take into account the actual values of all scores

median

### The mean is defined as

the mathematical center of the distribution

### To obtain the mean, we would

add all the scores (sigma X) and divide by the total number of scores (N)

mean

### The mean is the preferred measure of central tendency when

the distribution is symmetical and the scale of measurement is interval or ratio

symmetrical

### An experimenter investigated the ability to concentrate as a function of crowding. Concentration was measured as the amount of time it took the participant to complete a word puzzle. How should the experimenter summarize teh scores on the dependent variable?

Find the mean amount of time it took to solve the puzzle, if time scores are normally distributed.

### In a skewed distribution, the mathematical center is

the mean, which is not the point around which most of the scores tend to be located

### The mean is an inappropriate measure of central tendency when the distribution is severely skewed because

it does not accurately describe a skewed distribution

### When a distribution's mode > median > mean, it is said to be

negatively skewed

### When we refer to a score's deviation, we are referring to

how far it is from the mean

### What happens to the mean of a distribution if every score is divided by 10?

It's value is divided by 10.

### The mean si used most often in behavorial research because researchers tend to

measure variables that have interval or ratio scores, and the scores form approximately normal distributions.

### A deviation score of -3 indicates that the raw score is

less than the mean

0

### A score's deviation conveys two pieces of information about the score's location: the number indicates _____, and the sign indicates _____.

the score's distance from the mean, whether the score is greater or less than the mean

### The best predictor of an individual score in a sample of scores is the

mean of the sample of the scores

### When using the mean to predict scores, error is presented by

the deviation of a score from the mean

### When the mean is used to predict the scores, a deviation (X - X bar) indicates

the difference between the X bar we predict and the score an individual actually gets

### A deviation score is more informative than a raw score because it

gives the score's location relative to the mean

### With respect to a graph of a frequency distribution, a positive deviation score

will be located to the right of the mean

population mean

sample mean

### The population mean is estimated by

calculating the mean of a random sample drawn from the population

### When deciding which type of measure of central tendency is appropriate, we consider the scale of measurement used to measure the

dependent variable

### A researcher has conducted an experiment in which the independent variable is room temperature. Two conditions (a hot room and a cold room) were used. The dependent variable was the length of time required to complete a jigsaw puzzle. What is the best way to state that there is a relationship?

The mean times to complete the puzzle are different for the two rooms.

### In a graph of the relationship between the level of noise in an environment and the number of errors a person makes, the _____ is on the X axis and the ______ is on the Y axis.

level of noise, number of errors

### When deciding which type of graph is appropriate, we consider the characteristics of the

independent variable

### When we graph the results of an experiment, the Y axis indicates the

measure of central tendency we have used for the dependent variable

### When we graph results from an experiment, a line graph is appropriate when

the independent variable is ratio or interval

### On any graph a horizontal line of data points indicates that

the Y scores are not changing as the X scores change, and there is no relationship.

bar graph

bar graph

### If you see the notation "Sigma X squared" you should

square all the Xs, then sum the squares

### Measures of variability are used to

summarize and describe the extent to which scores in a distribution differ from one another

consistency

### Measures of central tendency indicate the _____ of a distribution while measures of variability indicate the _____ between the scores in a distribution

location, distance

### The greater the variability in a set of scores,

the less accurately the scores are represented by one central score.

### The range is the descriptive statistic that indicates the

distance between the two most extreme scores

the mean

### The average of the deviations can never actually be computed because

the sum of all deviations from the mean always equals zero

### When computing the variance, why do we square the deviations from the mean?

to compensate for the fact that deviations about the mean always sum to zero

### Variance is defined as the

average of the squared deviations around the mean

0

### If the variance for a sample is computed and it is found to be rather large, the numbers

are spread out around the mean

### Standard deviation is defined as the square root of the

average of the squared deviations around the mean

### The standard deviation is always

the square root of the variance

the mean

### The variance can never be

a negative number

### In roughly normal distributions, the standard deviation is approximately

one sixth of the range

### Adding or subtracting a constant from each of the scores in a distribution

does not change the value of the standard deviation

### Multiplying each of the scores in a distribution by a constant

multiplies the standard deviation by the same constant

underestimates

### Sample standard deviation and sample variance are considered biased estimates for the population standard deviation and variance because

they reflect the random variability of only N - 1 scores

### The quantity "N - 1" is known as the

degrees of freedom

larger than

### If we are going to predict future performance on the basis of a sample mean and the sample standard deviation, it is desirable to have a

small standard deviation

the variance

### In the language of statistics, when we know that a relationship exists between two variables, we can use knowledge of that relationship to

account for the variance

### The proportional improvement that resutls from using the relationship between two variables to predict scores compared with not using the relationship to predict scores is called

the proportion of variance accounted for.

### Of the three kinds of variances, which uses N-! in the final division?

estimated population variance

### The absolute value of a number is the

numeric magnitude of the number, regardless of whether is it positive or negative

### An evaluation of where a score is located in relation to other scores in the distribution reflects its

relative standing

### The z-score transformation is a useful statistical tool because it enables statisticians to

compare and interpret scores from virtually any distribution

### z-scores can be calculated from

interval or ratio scores

### z-scores communicate a score's

relative location in a distribution

### Given any z-score, it is safe to say that the absolute value is a good indicator of ______ and the sign is a good indicator of _____.

distance, direction

### A z-score of zero always means that

the raw score is equal to the mean

less frequently

### The distribution of z-scores is always

the same as the distribution of raw scores

0, 1

equal to 1

### When two normal z-distributions are plotted on the same graph, what can we say about the relative frequency of each z-score?

It will always be the same.

### The proportion of the total area under a normal curve between two z-scores corresponsd to the _____ of the range of scores.

relative frequency

### A theoretically perfect normal curve, which serves as a model of the perfect normal z-distribution, is called the

standard normal curve

### The relative frequency obtained from the standard normal curve is the _____ of the raw scores in our data, if the data formed a perfect normal distribution.

expected relative frequency

### How accurately the standard normal curve model predicts the actual relative frequency of raw scores depends on three aspects of data:

1) the raw scores form an approximately normal distribution, 2) there is a large sample N, 3) the raw scores are theoretically continuous scores measured on an interval or ratio scale

### We can use the standard normal curve as our model for

any approximately normal distribution, when transformed to z-scores

### In sampling distributions, all the samples contain sets of raw scores

that are representative of the population mean

### Which of the following statements accurately describes the sampling distribution of means?

The distribution of all possible sample means when an infinite number of samples of variously sized Ns are randonmly selected from several raw score populations.

### As the N of the samples used in a sampling distribution _____, the sampling distribution becomes _____.

increases, more like a perfect normal curve

### A sampling distribution is an approximately normal distribution

only when the shape of the raw score distribution is approximately normal

### Sampling distributions of means are always

approximately normally distributed

### The mean of the sampling distribution always equals

the mean of the underlying raw score population

normal

### The mean of the sampling distribution always equals

the mean of the underlying raw score population.

### The standard deviation of the sampling distribution of means is called the

standard error of the mean

Example: