exam 3 spss stuff

• A chi-square test is a statistical test used to compare observed results with expected results. The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying.
• The t-test .

  can be used to compare the mean differences between two groups onan interval- or ratio-level dependent variable
• The independent variable


  must be nominal and contain only two categories
• The most common use of the t-test in evaluating programs and practices is

  to compare the mean outcome scores of groups assigned to two different treatmentconditions (such as an experimental group versus a control group or a newtreatment versus a routine treatment).
• The one-sample t-test is

  a statistical hypothesis test used to determine whether an unknown population mean is different from a specific value.
• In order to use a one-sample t-test,

  we first have to know the populationparameter.
• The Paired Samples t Test


  compares the means of two measurements taken from the same individual, object, or related units
• We use the paired-samples t-test


  when the two groups of values that we want to compareare connected or related to each other in some way
• We use the independent-samples t-test


  when we want to compare the means of two independent groups. The term independent in this context means that the two groups to be compared are not connected or related to each other.
• The independent t test, also called unpaired t test, is


  an inferential statistical test that determines whether there is a statistically significant difference between the means in two unrelated (independent) groups
• degrees of freedom (df)


  refers to how many values are free to vary in a set of values if we know the summary statistic and the number of values in the set. (The size of the sample)
• SIGNIFICANCE in SPSS is

  the p-Vaule
• Parametric tests:


  At least one variable is interval or ratio level

  Variables are normally distributed

  Groups are independent of each other or randomly

  assigned
• Nonparametric tests:


  Variables are not interval or ratio level (some workwith just nominal or ordinal)Variables are not normally distributed
• F-ratio statistic


  : reflects the variation among the means ofseveral groups in relation to the variation within the groups
• variation BETWEEN groups (Numerator)•


  for each data value look at the difference between itsgroup mean and the overall mean (called between GroupsMean Square
• variation WITHIN groups (Denominator)•

  for each data value we look at the difference betweenthat value and the mean of its group (called within groupsmean square)
• Post hoc tests:


  used only when our F-ratio is

  significant
• ANOVA tells us there


  is a difference "somewhere"
• Post hoc testing is needed to


  determine where

  that "somewhere" is located

  (can't do multiple t-tests because it inflates our

  probability of a Type 1 error
• Two-way ANOVA


  Also called a factorial ANOVA
• Vertical line on a graph


  Might display different levels of a second variable, thus showing whether changing levels of categories on the variable on the horizontal axis move in a consistent fashion with changing levels of the second variable.
• Bar graphs


  Depict frequency distributions, using bars to show the number or percentage of cases for each category of a variable.
• Pie charts


  Portray frequency distribution data in terms of percentages represented by slices of a pie or sections of a circle.
• Histograms


  Look like bar graphs with bars that touch each other and can be used to depict frequencies with ordinal, interval or ratio level variables.
• Frequency polygons


  Typically involve interval- or ratio-level variables and use lines instead of bars.
• Line graphs can be misleading by


  Changing the spacing between categories on the vertical or horizontal axis so as to convey a more dramatic pattern or perhaps a less dramatic pattern, spreading out the distance between intervals on the vertical axis, and squeezing the intervals on the horizontal axis closer together, and squeezing the intervals on the vertical axis closer together while spreading out the intervals on the horizontal axis.
• X-axis on a graph


  The horizontal line that typically displays the values of a variable.
• Graphs that typically involve interval-or ratio-level variables

  Frequency polygons.
• When constructing line graphs, you should

  Avoid changing the spacing to make it fit your argument.
• Line graphs are useful when our purpose is to show trends over time


  N/A
• Horizontal line on a graph


  Called the x-axis or abscissa, and typically displays the values of a variable.
• Graphs and charts come in a variety of formats


  The format to use will depend on the purpose of the graph or chart.
• Point of origin on a graph


  The point at which the horizontal and vertical lines meet.
• Histograms can be used to depict frequencies with ordinal, interval or ratio level variables


  N/A
• EBP

  Provide example 

  EBP is engaged when a practice situation does not fit the typical or routine. For example, a substance abuse treatment program may routinely provide (evidence-supported) cognitive behavioral therapy (CBT) to clients whose goal is to become free of substance misuse.
• Descriptive 

  A descriptive statistic is a summary statistic that quantitatively describes or summarizes features from a collection of information, while descriptive statistics is the process of using and analysing those statistics
• influential observation is an observation for a statistical calculation whose deletion from the dataset would noticeably change the result of the calculation.
• Give 2 levels of measurements 

  Nominal: nominal" scale is a variable that does not really have any evaluative distinction

  Ordinal, Ordinal Scale is defined as a variable measurement scale used to simply depict the order of variables and not the difference between each variable.
• STANDARD DEVIATION