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24/25: MKTG212: Quantitative Marketing Research [1]

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95% of respondents will fall between the upper and lower limits (as determined by the regression using SPSS).

What is the lower limit? (To 2 decimal places)

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Assume a value of '5' for the independent variable ('My sub (sandwich) was delicious'). What is the value of dependent variable (predicted) - 'I would recommend Subsay to my friends'?  (Use 2 decimal places).

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Is the model significant?

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What is the value of the co-efficient of determination on the regression between 'My sub (sandwich) was delicious' and 'I would recommend Subsay to my friends'? (Three decimal places)

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Now run a regression using 'My sub (sandwich) was delicious' to predict 'I would recommend Subsay to my friends'. 

True or false.

The model using 'My sub (sandwich) was delicious is a better predictor of likelihood to recommend Subsay, than 'I felt satisfied after the sub' 

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True or false.

This is a useful model, that shows that if we improve 'satisfaction' having had a sub (sandwich) we could significantly improve the likelihood of exisiting customers recommending Subsay to their friends.

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Subsay knows that it can make the subs (sandwiches) bigger, so felt that they could address the issue of not  'feeling satisfied after the meal". Run a regression to determine how impactful this might be on the likelihood of a customer recommending Subsay. How good is the model. Put the value indicating how good the model is in the answer below. (Three decimal places).

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Considering only the items 'I would recommend Subsay to my friends' and 'My sub (sandwich) was delicious' with a correlation coefficient r = 0.37 (p <0.001).

How best would you illustrate this data in a chart? Select one from the options below:

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There is no indication that there is a linear association between 'feeling satisfied after the sub' (sandwich) and 'needing a snack to fill up'.

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Considering only the correlations with the item 'I would recommend Subsay to my friends', which items did NOT have a significant linear correlation? Tick as many as apply.

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