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Hello, please, I was given this project and seeking help from a tutor is totally allowed. Can you please go through it to see if

Hello, please, I was given this project and seeking help from a tutor is totally allowed. Can you please go through it to see if there is any help you can give. I will appreciate your help and guidance with this problems. Thanks

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Chapter 2: Generalizations: How Broadly do the Results Apply? Section 2.3: Errors & Significance PROJECT: PSYCHIC ABILITY Parapsychology Studies Statistician Jessica Utts has conducted an extensive analysis of Ganzfeld studies that have investigated psychic functioning. Ganzfeld studies involve a "sender" and a "receiver." Two people are placed in separate, acoustically-shielded rooms. The sender looks at a "target" image on a television screen which may be a static photograph or a short movie segment playing repeatedly) and attempts to transmit information about the target to the receiver. The receiver is then shown four possible choices of targets, one of which is the correct target and the other three are "decoys." The receiver must choose the one he or she thinks best matches the description transmitted by the sender. If the correct target is chosen by the receiver, the session is a "hit." Otherwise, it is a miss. Utts reported that her analysis considered a total of 2,124 sessions and found a total of 709 "hits" (Utts, 2010). 1. If the subjects in these studies have no psychic ability, what would be the long-run probability that the receiver would identify the correct target? 2. State the appropriate null and alternative hypotheses in both words and symbols for testing whether the data provide strong evidence of psychic ability. [Hint: The wording in #1 should help with this.] 3. Calculate the proportion of "hits" (successful transmissions of the target image) among the 2,124 sessions that the researcher analyzed. Use the appropriate symbol. Is this proportion larger than the null-hypothesized value for the probability of a successful transmission? 4. Use a simulation-based method to determine an approximate p-value for testing the hypotheses stated in #2. approximate p-value =

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