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EXPERIMENTAL DESIGN

prisha patel English 42 cards

Cards in this deck (42)

  1. 1experimental designThe way in which participants are allocated to levels of IV
  2. 2experimental designThe way in which participants are allocated to levels of IV
  3. 3experimental designThe way in which participants are allocated to levels of IV
  4. 4experimental designThe way in which participants are allocated to levels of IV
  5. 5experimental designThe way in which participants are allocated to levels of IV
  6. 6experimental designThe way in which participants are allocated to levels of IV
  7. 7experimental designThe way in which participants are allocated to levels of IV
  8. 8the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  9. 9the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  10. 10the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  11. 11the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  12. 12the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  13. 13the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  14. 14the participants may be allocated to all or only 1 of the levels of IV3 types of experimental designs are :
    - independent measures design
    - repeated measures design
    -matched pairs design
  15. 15independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  16. 16independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  17. 17independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  18. 18independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  19. 19independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  20. 20independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  21. 21independent measures design - an experimental design in which a different group of participants is used for each level of IV- a separate group of participants is used for each level of IV
    - data for each level of IV is independent because it's not related to any other data, it has come from different people
    example of independent measures design
    * if we wanted to know whether seeing aggressive models on TV has long term effects we could compare 2 groups of adults 1 who had been allowed to watch aggressive TV as children and 1 group who hadn't been allowed and this would be quicker
    EVALUATION
    * design is good bcoz participants only encounter experimental setting once so they are therefore unlikely to notice or respond to clues that might tell them aims of experiment (demand characteristics)
    - 1 problem is there might be individual differences between participants that could influence findings - risk can be reduced by random allocation of participants
  22. 22independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  23. 23independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  24. 24independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  25. 25independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  26. 26independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  27. 27independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  28. 28independent measures design* random allocation of participants to different conditions can reduce risk of individual differences - spreads possible differences between individuals across levels of IV
    * to randomly allocate participants, each person is given a number and the numbers are then randomly divided into 2 groups
    it can be done by telling each participants a number or putting numbers into a hat and drawing out 2 sets or using random number generator
    RANDOM ALLOCATION - WAY TO REDUCE EFFECT OF CONFOUNDING VARIABLES SUCH AS INDIVIDUAL DIFFERENCES, PARTICIPANTS ARE OUT IN EACH LEVEL OF IV SUCH THAT EACH PERSON HAS AN EQUAL CHANCE OF BEING IN ANY CONDITION
  29. 29repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  30. 30repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  31. 31repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  32. 32repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  33. 33repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  34. 34repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  35. 35repeated measures design - an experimental design in which each participants performs in every level of IV- same group of participants participate in every level of IV
    * participants are repeating their performance under different conditions
    EVALUATION
    *main advantages is that each person acts at their own baseline, any differences between participants that could influence their performance and therefore DV will affect both levels of IV same way ,individual differences are therefore unlikely to bias findings
    * individual differences between participants are called PARTICIPANT VARIABLES, these variables such as age, gender, personality or intelligence can affect scores on Dv ,it's therefore important to make sure that these variables don't hide or exaggerate, differences between levels of IV
    PARTICIPANTS VARIABLES - INDIVIDUAL DIFFERENCES BETWEEN PARTICIPANTS THAT COULD AFFECT THEIR BEHAVIOUR IN A STUDY ,THEY COULD HIDE OR EXAGGERATE DIFFERENCES BETWEEN LEVELS OF IV
  36. 36repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  37. 37repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  38. 38repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  39. 39repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  40. 40repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  41. 41repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing
  42. 42repeated measures design* as each individual participates in every level of IV they will perform the same or similar tasks 2 or more times ->leads to a problem called order effect ,repeated performance could cause participants to improve because they have encountered task before -practice effect, this would matter because participants who were tested on a condition seconds would perform better than those who did first . repetition might also make a performance worse perhaps if they were bored or tired- fatigue effect
    * participants see both levels of iv and have more opportunity to work out what is being tested so are more likely to respond to demand characteristics
    *order effect can be solved in 2 main ways
    -randomisation
    - counterbalancing

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Flashcards on EXPERIMENTAL DESIGN , created by prisha patel on 12/04/2019.
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