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# MKT 302 Exam 1 Study Guide MKT 302

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This 12 page Study Guide was uploaded by taylor Notetaker on Wednesday September 23, 2015. The Study Guide belongs to MKT 302 at University of Miami taught by Tsiros in Fall 2015. Since its upload, it has received 42 views. For similar materials see Marketing Research in Marketing at University of Miami.

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Date Created: 09/23/15

MKT 302 Exam 1 Study Guide Marketing Research 0 The function linking the customer and public to the marketer through information o The process of turning data into information used for decision making 0 Data that are gathered analyzed and reported which are used to solve a marketing problem or address a business issue Management Decision Problem vs Marketing Research Problem 0 Management Decision Problem 0 What the decision maker needs to do 0 Action oriented o Focuses on symptoms 0 Examples Should a new product be introduced Should the ad campaign be changed Should the price be increased 0 Marketing Research Problem 0 What information is needed and how it should be obtained 0 Information oriented o Focuses on underlying causes 0 Examples Determine consumer preferences and PI for NP Determine effectiveness of current ad campaign Determine price elasticity of demand and the impact on sales and pro ts at various levels of price changes Conceptual Map Management wants to TAKE AN ACTION Therefore we should study TOPIC So that we can explain QUESTION Marketing Research s Role in the Business Triangle Company l EXTERNAL l Customer Customer l l INTERACTIVE l Employee Employee l INTERNAL l Company Decisions that Draw on Marketing Research Segmentation deciding which and where segments should be targeted and their bene ts 0 Product determining features packaging and desired market position 0 Distribution determining type of distribution setting margins intensity of coverage 0 Advertising and Promotion determining how much to spend and on which media outlets MKT 302 Exam 1 Study Guide 0 Personal Selling setting goals and sales force territories and number of sales staff 0 Price setting level responding to competitors using pricing strategies Branding building and capitalizing on brand equityloyalty Customer Satisfaction deciding on how to measure it and developing a strategy to respond Factors In uencing Marketing Research Decisions 0 Relevance 0 Timing TypeNature of Information sought 0 Resource Availability CostBene ts Analysis Supplier Ethics LowBall Pricing Allowing Subjectivity Violating Con dentiality Abusing Respondents Up Selling Unnecessarily Why Use Statistics 0 Increasing use of quantitative approach by sciences and business inventory planning analysis of traf c patterns 0 More data collected processed and disseminated to the public Descriptive Statistics Presentsummarize data table or graph 0 Example 60 of all companies employ fewer than 100 employees lnferential Statistics Predict market share of a product not yet introduced in the market Nature of Statistical Data 0 Nominal 0 Numerical in name only MKT 302 Exam 1 Study Guide 0 Numbers identify the object and that is all boy 1 girl 2 0 Do not share properties of numbers eg 3gt1 0 Also called arti cial or categorical data 0 Example marital status boygirl ethnicity 0 Ordinal 0 Setting up inequalities is permitted eg 3gt1 but not 43 21 0 Example educational background elementary middle high college 0 Interval 0 Comparisons are permitted but cannot multiply or divide eg 68 63 131 126 but NOT 126 twice as hot as 63 o Arbitrary zero absence of temperature 0 126 F 52 C 63 F 17C 126 263 but 52 317 0 Example temperature 0 Ratio 0 Can form quotients 0 Example weight Scales of Measurement 0 Scale Nominal Basic Comparisons Identity Ex Malefemale occupations Measures of Averages Mode 0 Scale Ordinal Basic Comparisons Order Ex brand pref social class Measures of Averages Mode Median Scale Interval Basic Comparisons Comparison of intervals Ex temp scale GPA attitude towards brands awareness of advertising Measures of Averages Mode Median and Mean 0 Scale Ratio Basic Comparisons Comparison of absolute magnitudes Ex units sold of purchasers prob of purchase weight Measures of Averages Mode median mean Review of Basic Statistics 0 When we deal with large sets of data a good overall picture can be conveyed by grouping the data into a number of classes intervals or categories 0 Whenever possible we try to make categories cover equal ranges of values 0 The most common form of a graphical presentation is the histogram or the bar chart 0 Population a set of data that consists of all conceivably possible observations of a given phenomenon Sample a set of data that consists of only a part of all conceivably possible observations of a given phenomenon 0 Measures of Central Location 0 Mean always exists always unique further statistical treatment takes into account all the data Mean Sum of Xi N Standard Deviation sqrt sum xxbarsqred N1 MKT 302 Exam 1 Study Guide 0 Median the value of the middle item when n is odd and the mean of the middle items when n is even 0 Mode the value which occurs with the highest frequency requires no calculation can be determined for nominal data may not exist may not be unique Reliability and Validity A neither reliable nor valid measure 0 A reliable but not valid measure A reliable and valid measure 0 Overview of Data Analysis Procedures Step 1 0 Validation con rming the interviewssurveys occurred 0 Editing determining the questionnaires were completed correctly Step 2 Coding grouping and assigning numeric codes to the question responses Coding list and consolidate responses set and enter codes Step 3 0 Data Entry process of converting data to an electronic form 0 Data Entry can use scanning devices to enter data Step 4 0 Clean the Data check for data entry errors or data entry inconsistencies Step 5 0 Data tabulations and statistical analysis MKT 302 Exam 1 Study Guide 0 Cross tabulations charts graphs descriptive statistics etc Cross Tabulations examination of the responses to one question relative to the responses to one or more questions in a survey set Pivot Table in Microsoft Excel BiVariate Cross tabulation of two items Business Category and Gender MultiVariate Cross tabulation of additional ltering criteria now ltering three or more Descriptive Statistics effective means of summarizing large sets of data 0 Key measures include Mean Median Mode Kurtosis Standard Deviation Skewness Variance Signi cant discrepancies between Mean and Median should cause you to look at data further Evaluating Differences and Changes 0 Mathematical Differences by de nition if numbers are not exactly the same they are different THIS DOES NOT HOWEVER mean that the difference is either important or statistically signi cant 0 Statistical Signi cance if a particular difference is large enough to be unlikely to have occurred because of chance or sampling error then the difference is statistically signi cant Managerially Important Differences one must be able to distinguish between mathematically signi cant differences and statistically signi cant difference in using the data analysis in managerial decision making Hypothesis an assumption argument or theory that a researcher or manager makes about some characteristics of the population under study Which Analysis to Perform MKT 302 Exam 1 Study Guide Dependent Variable is nolnstnetrie Dependent Variable is metric Nominal or Ordinal Interval or Ratio Eg Yes vs Nu Egg Agree 1 2 3 4 5 Disagree Independent Variable is ChiSquare 32 Nonmetric with two levels Crosstabs tetest Yes vs No Independent Variable is ChiSquare 38 N innmetric with more than We levels Cmssmbs AN OVA Lew vs Medium vs High Independent Variable is metric Correlation Agree 1 2 3 4 5 Disagree Logis e regression Regression Steps in Hypothesis Testing Step 1 Stating the Hypothesis Null Hypothesis status quo proven to be true 0 Alternative Hypotheses another alternative proven to be true Step 2 Choosing the Appropriate Test Statistic Test of means test or proportions ANOVA etc Step 3 Developing a decision rule 0 Determine the signi cance level Needed to determine whether to reject or fail to reject the null hypothesis Step 4 Calculating the Value of the Test Statistic Use the appropriate formula to calculate the value of the statistic Step 5 Stating the Conclusion Stated from the perspective of the original research question Types of Errors in Hypothesis Testing 0 Type I Rejection of the null hypothesis when in fact it is true 0 Type II Acceptance of the null hypothesis when in fact it is false 0 Issues with the types of errors MKT 302 Exam 1 Study Guide Type I amp Type Ill Errors Actual Stateof the Fa to Raj est H0 Raj eat H Null Hypothesis 0 lltll0 is true Correct 1 1 Type I error or no error H0 is false Type 11 error B Correct 1 3 no error One Vs TwoTailed Hypotheses Tests are either one or twotailed this depends on the nature of the situation and what the researcher is demonstrating OneTailed quotIf you take the medicine you will get betterquot TwoTailed quotIf you take the medicine you will either get better or worse but not stay the samequot Commonly Used Statistical Hypothesis Tests 0 Independent Samples samples in which measurement of a variable in one population has no effect on measurement of the variable in the other ChiSquare Test test of goodness of t between the observed distribution and the expected distribution of a variable 0 Answers the question Does the observed pattern of frequencies correspond to an expected patternquot Hypotheses Tests about One Mean ZTest hypothesis test used for a single mean if the sample is large enough and drawn from a normal population 0 Usually for samples 30 tTest hypothesis test used for a single mean if the sample is too small to use the Ztest 0 Usually for samples below 30 Hypotheses Tests about Two Means hypothesis testing that tests the difference between groups of data Bivariate Analysis of Association MKT 302 Exam 1 Study Guide 0 Bivariate Techniques statistical methods of analyzing the relationship between two variables 0 Independent Variable symbol or concept that the researcher has some control over or can manipulate to some extent and that is hypothesized to cause or in some way in uence the dependent variable 0 Dependent Variable symbol or concepts expected to be explained or caused by the independent variable 0 Bivariate Regression Analysis the analysis of the strength of the linear relationship between variables when one is considered the independent variable and the other is the dependent variable Scatterplots Conveyance of Linear Relationships Perfect Positive Relationship Between X and Y Perfect Negative Relationship Between X and Y Perfect Parabolic Relationship Between X and Y LeastSquares Estimation Procedure 0 LeastSquare Estimation 0 Used to t data for X and Y 0 Results in a straight line that ts the actual observations plotted dots better than any other line that could be t to the observations MKT 302 Exam 1 Study Guide 7 LeastSquares Estimatlen Procedure Estiman ng the best line of t Y 6 3 Where Y dependent variable a estimated Y intercept l estimated slope of the regression line 1 X 3 independent variable E E BITDI values fora and b can be calculated as follows Where I 3 mean of value X h 2 Xi Yi nXY b Y mean of value y 2 xzi 002 a V b 11 2 sample else Statistical Significance of Regression Results Y Xvii liabX1 l m Unexplained Veal13 l Variation r39 i Explained Variation 39 Y X Y A J 0 X X MKT 302 Exam 1 Study Guide Measures of Association Coefficient of Determination R3 Percentage of the total variation in the dependent variable explained by the independent variable 2 a Total Variation Unexplilined Var imion R 39 Total Variation n Z Yi quot Yi 2 R2 1 l n r gm Y 2 Pearson Correlation Analysis of the degree to which changes in one variable are associations with changes in another for use with metric data Ror R27 Spearman Correlation Correlation analysis technique for use with ordinal data For rank order measure of association Assessing Measures of Association 0 Measures of Association 10 0 Does not mean there is a casual relationship between the relevant variables Could simply represent coincidence between the relevant variables 0 0 Should be taken in context and with the timeliness of both data sets in mind 0 Can be used in conjunction with cross tabulations of the relevant data to add another perspective to the results Multivariate Analysis Procedures 0 Multiple Regression Analysis a procedure for predicting the level of magnitude of a dependent variable based on the levels of multiple independent variables 0 one can predict the magnitude of a dependent variable based on the levels of more than one independent variable 0 Application Estimating various marketing mix variables Estimating the relationships between variables Determine relative in uences among satisfaction elements Rate the relative strength on factors deemed important etc Determine the strength of various variables on consumer behavior S 9 quot 11 MKT 302 Exam 1 Study Guide Quantifying the relationship between classi cation variables Ascertaining which variables are predictive of dependent variable changes 0 Measures of Multiple Regression Analysis Coef cient of Determination measure of the percentage of the variation in the dependent variable explained by variations in the independent variables Regression Coef cients Estimates of the effect of individual independent variables on the dependent variables 0 Dummy Variables inclusion of nominalscaled independent variables to add richness to the analysis 0 Factor Analysis enables one to reduce a set of variables to a smaller set of factors or composite variables by identifying underlying dimensions of data Conjoint Analysis provides a basis for estimating the utility consumers associate with different product features or attributes Potential Problems with Regression Collinearity correlation of independent variables with each other which can bias estimates of regression coef cients Causation inference that a change in one variable is responsible for or caused an observed change in another variable might be false 0 The Sample the sample size might be too small or it might not be representative of the population and the researcher thinks it is MKT 302 Exam 25 multiple choice 3 or 4 problems analyze outputs from SPSS and describe NO CALCULATIONS go through slides and go through notes up to end of day 6 ANOVA IS NOT ON THIS EXAM Sample Exam Answers C regression analysis correlation does not assume dependency and it is only between 2 variables E simple regression equation y a bx C reversely correlated if negative number and close to 1 A nominal gender ethnicity numbers identify object and that is all boy 1 girl 2 D multiplicationdivision B Chi squared tests frequencies deal with nominal and ordinal data E ordinal levels of education 12 MKT 302 Exam 1 Study Guide Three Steps to Answer Question regardless which test it is State the null hypothesis Hsub0 Report the relevant statistics Make a decision retain or reject null hypothesis Ttest compares two means identify the two variables means dollar paid of last tune up Null Hypothesis there is no difference between the means of dollars paid for cash and dollars paid for credit card mean mu Step 1 Hsub0 Mcredit Mcash Steps 2 and 3 ttestt 975 sig 2tailed is pvalue compare to 05 reject if less 338 RETAIN Null because greater gt 05 chi squared test looks at frequencies must actually write out in english down to cross tabs info Null hypothesis no differences Hsub0 Gas type is independent of oil type OR a couple other ways to write chi squared value Pearson ChiSquare 621 Retain Asymp Sig 2 sided because 431 gt 05 correlation test both variables are interval or ratio are dollars and miles driven related Null hypothesis Hsub0 r 0 correlation between two variables is zero unrelated r 017 Retain because sig is 928 gt 05 thus no relationship between two variables regression test write equation for step 2 rst because may help Step 1 Null hypothesis Hsub0 x123 and y are not correlated zero correlation no relationship b10b20b30 Step 2 go to coef cients B values quuared 488 y1937694 109559x1age 048x2 5123x3 gallons Step 3 retain if gt 05 reject if lt 05 SO bl 0 reject 109 gt 00 lt 05 b2 0 retain 048 gt 969 gt 05 b3 0 retain 5123 gt 838 gt 05

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