A finished MKT-445 Topic 6 survey data analysis plan example, assigning each cinema survey item a measurement level, the statistics it permits and a dummy table tied to the seating decision. Searches like "mkt 445 topic 6 assignment example", "mkt445 topic 6 sample" and "mkt-445 topic 6 example" land here.
What a finished MKT-445 Topic 6 survey data analysis plan looks like
Written before any data exists, which is its point, the finished plan lists the questionnaire's fourteen items and classifies each using the four levels Stevens described: nominal, ordinal, interval and ratio. Which theater a respondent visits most is nominal, so it gets frequencies and cross-tabulations with a chi-square test. Agreement statements on a five-point scale are ordinal, and the plan reports their distributions, medians and top-two-box shares instead of means. Visits in the past three months and the extra price a respondent would pay per ticket are ratio, so means, confidence intervals and a regression are allowed. For the one seven-point scale the chain wants averaged, the plan states that treating it as interval is an assumption and prints the distribution beside the mean. Dummy tables show every planned output with empty cells.
How an MKT-445 Topic 6 example is structured
Decision, items and outputs are taken in that order. The opening section states the conversion decision and the three figures it depends on: how many regular moviegoers would pay a premium, how much more, and whether they would visit more or less often. A measurement table follows, listing each item, its response format, its level and the statistics that level permits. A section on the contested case, averaging the seven-point comfort scale, explains the assumption and how the report will disclose it. The tests section names each comparison planned, such as premium willingness by frequency of visits, with the test chosen and why. Dummy tables come next, one for each figure the decision needs, with column headings and empty cells. Last comes a list of analyses deliberately left out, so that any later exploration is reported as exploration.
Written before any response arrives
Fixing tables and tests ahead of fieldwork keeps the analysis from drifting toward whichever comparison happens to look striking once the data comes in.
Every item given its level
A table classifies all fourteen questions as nominal, ordinal, interval or ratio, and lists beside each the statistics that level can legitimately support.
Agreement scales reported as distributions
Five-point agreement items appear as full distributions, medians and top-two-box shares, since a mean would assume equal spacing the scale never promised.
One averaged scale, disclosed
The chain wants a mean comfort score, so the plan computes it, labels the interval assumption and shows every response category next to the average.
Dummy tables with empty cells
Each figure the decision depends on appears as a blank table with its rows and columns set, so the report's shape is agreed before the numbers.
Unplanned analyses marked as exploration
Comparisons not listed in advance may still be run, and the plan requires them to be reported as exploratory findings rather than as tested ones.
Where marks go in MKT-445 Topic 6
Means computed from every rating scale without comment are penalized first, since ordinal answers do not guarantee equal distances between options and the average quietly assumes they do. Naming the levels of measurement in a paragraph and then never classifying the actual items leaves the theory disconnected from the questionnaire. Drafts often choose tests by habit, a t-test for everything, when the chosen comparison involves nominal categories that call for a cross-tabulation. Analysis plans written after the data arrives invite the charge that comparisons were selected for their results. Tables that do not map to the decision's figures produce output the chain cannot use. Treating an exploratory finding as though it had been planned overstates its strength, which the course typically returns to in its closing topic.
Get an MKT-445 Topic 6 example written to your instructions
Send the MKT-445 Topic 6 instructions and the rubric shared in your classroom, with the questionnaire or data your section supplied. We write a custom example to them, with every item assigned a measurement level, statistics matched to each, contested averages disclosed and dummy tables tied to the decision, in 24 to 48 hours. The first one is free.
MKT-445 Topic 6 questions, answered
What are the four levels of measurement?
Nominal scales name categories with no order, such as a preferred theater. Ordinal scales rank without guaranteeing equal gaps, such as agreement from strongly disagree to strongly agree. Interval scales have equal gaps and no true zero, such as temperature in Fahrenheit. Ratio scales have equal gaps and a true zero, such as dollars or visits. The classification comes from S. S. Stevens, and each higher level permits everything the lower ones do.
What is a dummy table?
A table drawn before data collection with its title, rows and columns labeled but every cell left blank. It shows exactly what the analysis will produce and lets the decision-maker confirm those outputs are the ones needed. Dummy tables also reveal missing questions early: if a planned table requires a variable the questionnaire never asks for, the gap appears while it can still be fixed.
What is a top-two-box score?
The share of respondents choosing the two most favorable options on a rating scale, such as agree and strongly agree. It is widely used in marketing research because it summarizes an ordinal item without assuming equal intervals, and managers find a percentage easy to read. Its weakness is that it discards the difference between neutral and negative answers, so the example reports the full distribution as well.