School

Jackson State University **We aren't endorsed by this school

Course

PSY 310

Subject

Statistics

Date

Sep 25, 2023

Type

Other

Pages

4

Uploaded by SuperSnowCaribou14 on coursehero.com

Definitions
statistics-
a set of mthematical procedures for organizing, summarizing, and interpreting data.
distinguish sample and population-
●
population is the entire group of individuals where the information is being derived.
●
Sample is a subset of the population.
2 methods of statistics and the difference between the too (descriptive vs inference)-
●
Descriptive statistics are statistical procedures used to summarize, organize, and
simplify data.
●
Inference consists of techniques that allow us to study samples and then make
generalizations about the population from which they are selected.
sample error-
the naturally occuring error that exsists between a sample stastic and the
corresponding population parameter.
type 1 error and type 2 error-
●
Type I error occurs when a researcher rejects a null hypothesis that is actually true. In a
typical research situation, a Type I error means the researcher concludes that a
treatment does have an effect when in fact it has no effect.
●
Type II error occurs when a researcher fails to reject a null hypothesis that is really false.
In a typical research situation, a Type II error means that the hypothesis test has failed to
detect a real treatment effect.
variable-
a characteristic or condition that changes or has different values for different
individuals.
difference between independent an dependent-
●
Independent variable is the variable that is manipulated by the researcher.
●
Dependent variable is the variable that is observed to access the effect of the treatment
research methods (experimental, nonexperimental, and correlation)-
●
Experimental method is giving medicine. One variable is manipulated while the other is
being observed and measured. An experiment attempts to control all other variables to
prevent them from influencing the results.
●
Correlation method 2 different variables are observed to determine whether there is a
relationship between them.
●
Nonexperimental study does not permit a cause/effect explaination. It also doesn't give
medicine.
discret and contiuous know the difference-
●
Discret consists of separate indivisible categories, no values can exist between 2
neighboring categories.
●
Contiuous are infinite numbers of possible values that fall between any 2 observed
values. Its divisible into an infite number of fractional parts.
know the 4 scales of measurements-
●
Nominal scale consists of a set of categories that have 4 different names.Measurments
on a nominal scale lable and categorize observations but do not make any quantitative
distinctions between observations.
●
Ordinal scale consists of a set of categories that are organized in an ordered sequence.
Measurements on an ordinal scale rank observations in terms of size or magnitude.
●
Interval scale consists of ordered caregories that are all intervals of exactly the same

size. Equal diferences between numbers on scale reflect equal differences in magnitude
however, the zero point on interval scale is arbitrary and does not indicate a zero amount
of the variable being measured.
●
Ratio scale is an interval scale with the aditional feature of an absolute zero point. With a
ratio scale, ratios of numbers do reflect ratios of magnitude
difference between a histogram, polygram, and bar graph-
●
Histogram is contiuous data. It looks like a bargraph execpt all information is connected.
●
Polygon looks like a line graph.
●
Bar graph looks like a histogram but the information is separate.
know positively screw and negatively screw-
●
Positively skew data has a tail pointing towards the right hand side of the graph.
●
Negatively skew data has a tail pointing towards the left hand side of the graph.
definition for mean, median, mode (they are the central tendacy measurement)
●
Mean is the sum of the scores divided by the number of scores.
●
Median is the midpoint of the list.
●
Mode is the score or category that has the greatest frequency.
central tendacy ( what type of measurement is it)-
is a statistical measure to determine a single
score that defines the center of distribution. The goal of central tendency is to find the single
score that is most typical or most representative of the entire group.
variability-
provides a quantitative measure of the differences between scores in a distribution
and describes the degree to which the scores are spread out of clustered together.
variance and standard deviation-
●
Standard deviation is the distance from the mean.
●
Variance equals the mean of the squared deviation. Variance is the average square
distance from the mean.
bias vs unbias statistic-
●
A sample statistic is biased if the average value of the statistic either underestimates or
overestimates the corresponding population parameter.
●
A sample statistic is unbiased if the average value of the statistic is equal to the
population parameter.
z-score (what does it give us about the data)-
is the number of times standard deviation away
from the mean. It tells the exact location of the x value. The mean of z is always zero.
probability-
a fraction or a proportion of all the possible outcomes.
hypothesis (steps of hyposthesis are listed)-
A hypothesis test is a statistical method that uses
sample data to evaluate a hypothesis about a population.
Step 1- state the hypothesis.
Step 2- Set the criteria for a decision.
Step 3- collect data and compute sample statistics.
Step 4- accept or reject your null.
randomly sampled-
requires that each individual in the population has an equal chance of being
selected.
what does SPSS stand for, whats the alternative, and what's the latest verion-
SPSS stands for 'statistical package for the social sciences' and the latest version is 28. Its
alternative is excel or SAS.

Equations:
frequency distribution table know how to read it (will use it to calculate on the test)
Independent and dependent hypothesis examples:
(ho: pie=35 hi:pie doesn't =35 is a dependent study)
(ho: m1-m2=0 hi:m1-m2 doesn't equal 0 is an independent study)
know how to solve for:
if i give you an x, whats the z-score
if i give you a z whats the x
Probability example:
m=45
std.=4
p(x greaterthan 43)
Z= x-m/std.
43-45/4= -.5 = .6915 =69%
sample data
10, 7, 6, 10, 6, 15
1.
find SS ss=sumofx squ - (sumofx)squ/n 54^2/6=486
2.
variance SS-n-1=12
3.
std (squarerootof 12)
mathematical operations
sumofx =14
sumofx^2 (no parenthesis is individually)=48
(sumofx)^2 (Parenthesis is the whole sum)=14^2
sumofx+5=19
sumof(xt5)=39
x
x^2
(x)^2
x+5
x+5
3
9
8
2
4
7
5
25
10
1
1
6
3
14
9
48
8
38